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The opportunity
At Unity, we’re shaping the future of real-time 3D development by enabling creators to harness intelligent, autonomous systems. Our next-generation agentic AI - goal-directed, adaptive, and capable of reasoning and planning in dynamic environments - is transforming how games and simulations come to life.

We’re looking for a Staff Machine Learning Engineer to lead the development of these foundational AI systems within the Unity engine, empowering creators to build smarter, more responsive in-game agents and simulations. Your work will directly drive innovation, allowing developers and designers to integrate sophisticated AI behavior seamlessly into their worlds.

This role is perfect for someone passionate about pushing the boundaries of AI, multi-agent systems, reinforcement learning, and intelligent decision-making in complex, real-time environments.

What you'll be doing

Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors.
Define orchestration logic for single- and multi-agent systems
Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility.
Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling systems for persistent, believable behavior.
Collaborate across internal and external teams to unlock innovative use cases in gaming, simulation, and interactive storytelling.
Contribute to the long-term vision and roadmap for Unity’s agentic AI offerings, ensuring modularity, usability, and performance across platforms.
Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments.
Experience with multi-agent systems, orchestration, or AI tool integration.
Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems.
Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Strong system design skills and the ability to architect performant, scalable ML systems.
Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers.

You might also have

Familiarity with game development workflows.
Publications or open-source contributions in reinforcement learning, agent-based modeling, or related areas.
Experience with behavior trees, utility AI, or hierarchical task planning.
Passion for the gaming industry and AI applications in games.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Unity [NYSE: U] is the leading platform to create and grow games and interactive experiences. Creators, ranging from game developers to artists, architects, automotive designers, infrastructure experts, filmmakers, and more, use Unity to bring their imaginations to life across multiple platforms, from mobile, PC, and console, to spatial computing.

As of the third quarter of 2024, more than 70% of the top 1,000 mobile games were made with Unity, and in 2024, Made with Unity applications had an average of 3.7 billion downloads per month. For more information, please visit Unity.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#Sen #Li-Ar1

*Note: Certain locations require a good faith disclosure of the base salary range for the role. The actual salary for the successful candidate may differ based on location, experience, and other job-related factors.

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":2,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

This role is perfect for someone passionate about pushing the boundaries of AI, multi-agent systems, reinforcement learning, and intelligent decision-making in complex, real-time environments.

What you'll be doing

Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors.
Define orchestration logic for single- and multi-agent systems
Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility.
Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling systems for persistent, believable behavior.
Collaborate across internal and external teams to unlock innovative use cases in gaming, simulation, and interactive storytelling.
Contribute to the long-term vision and roadmap for Unity’s agentic AI offerings, ensuring modularity, usability, and performance across platforms.
Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments.
Experience with multi-agent systems, orchestration, or AI tool integration.
Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems.
Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Strong system design skills and the ability to architect performant, scalable ML systems.
Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers.

You might also have

Familiarity with game development workflows.
Publications or open-source contributions in reinforcement learning, agent-based modeling, or related areas.
Experience with behavior trees, utility AI, or hierarchical task planning.
Passion for the gaming industry and AI applications in games.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":3,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

This role is perfect for someone passionate about pushing the boundaries of AI, multi-agent systems, reinforcement learning, and intelligent decision-making in complex, real-time environments.

What you'll be doing

Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors.
Define orchestration logic for single- and multi-agent systems
Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility.
Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling systems for persistent, believable behavior.
Collaborate across internal and external teams to unlock innovative use cases in gaming, simulation, and interactive storytelling.
Contribute to the long-term vision and roadmap for Unity’s agentic AI offerings, ensuring modularity, usability, and performance across platforms.
Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments.
Experience with multi-agent systems, orchestration, or AI tool integration.
Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems.
Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Strong system design skills and the ability to architect performant, scalable ML systems.
Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers.

You might also have

Familiarity with game development workflows.
Publications or open-source contributions in reinforcement learning, agent-based modeling, or related areas.
Experience with behavior trees, utility AI, or hierarchical task planning.
Passion for the gaming industry and AI applications in games.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":4,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

This role is perfect for someone passionate about pushing the boundaries of AI, multi-agent systems, reinforcement learning, and intelligent decision-making in complex, real-time environments.

What you'll be doing

Design, implement, and scale AI agents that assist in generating game code and executing goal-directed behaviors.
Define orchestration logic for single- and multi-agent systems
Develop reusable agentic frameworks - planning modules, memory systems, or policy adaptation layers - for creator extensibility.
Lead high-impact initiatives, including hierarchical reinforcement learning for scalable behaviors, AI planning and goal inference frameworks for NPCs and simulations, and agent memory and world modeling systems for persistent, believable behavior.
Collaborate across internal and external teams to unlock innovative use cases in gaming, simulation, and interactive storytelling.
Contribute to the long-term vision and roadmap for Unity’s agentic AI offerings, ensuring modularity, usability, and performance across platforms.
Establish and champion best practices for model quality, simulation-based evaluation, and ML/AI safety within real-time systems.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, or a related field.
5+ years of hands-on experience developing ML systems in production, ideally within real-time or interactive environments.
Experience with multi-agent systems, orchestration, or AI tool integration.
Strong background in one or more of the following: LLM, reinforcement learning, decision-making under uncertainty, AI planning, or multi-agent systems.
Proficiency in at least one general-purpose programming language (e.g., Python, C++, Go, Java) and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Strong system design skills and the ability to architect performant, scalable ML systems.
Excellent communication and collaboration skills; ability to work effectively with cross-functional teams including engine developers, designers, and product managers.

You might also have

Familiarity with game development workflows.
Publications or open-source contributions in reinforcement learning, agent-based modeling, or related areas.
Experience with behavior trees, utility AI, or hierarchical task planning.
Passion for the gaming industry and AI applications in games.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":5,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - Recommender systems","datePosted":"2025-09-19","description":"

Why Playstation?

PlayStation isn’t just the Best Place to Play — it’s also the Best Place to Work. Today, we’re recognized as a global leader in entertainment producing The PlayStation family of products and services including PlayStation®5, PlayStation®4, PlayStation®VR, PlayStation®Plus, acclaimed PlayStation software titles from PlayStation Studios, and more.

PlayStation also strives to create an inclusive environment that empowers employees and embraces diversity. We welcome and encourage everyone who has a passion and curiosity for innovation, technology, and play to explore our open positions and join our growing global team.

The PlayStation brand falls under Sony Interactive Entertainment, a wholly-owned subsidiary of Sony Group Corporation.

Machine Learning Engineer, Recommendation System

Do you want to join a Machine Learning team committed to personalizing the PlayStation experience for hundreds of millions of users? We deliver impactful ML models and systems that serve an increasingly dynamic and personal experience! The Machine Learning Engineers within the DTIS group will deliver optimized interactions across PlayStation experiences and systems by designing, coding, training, deploying, and evaluating very large-scale machine learning systems.

We are looking for someone who can build delightful products and experiences for millions, in an agile environment, collaborating with teams across Engineering, Product, and Business. Further, you will be immersed in groundbreaking ML technologies, tools and processes, as you help to advance our technical objectives and architectural initiatives.

You Will:

Design and develop various machine learning and deep learning models and systems for high-impact consumer-facing applications such as content personalizations and product recommendations.
Work with a broad spectrum of state-of-the-art machine learning and deep learning technologies in the areas of recommendation systems.
Create metrics and design A/B test plans to evaluate model performance offline and online to inform and convey our impacts to diverse groups of stakeholders.
Collaborate with cross-functional teams of technical members and non-technical members in architecture, design, and code implementations.
Analyze and produce insights from a large amount of dynamic structured and unstructured data using modern big data technologies.
Produce reusable code and conduct peer code reviews according to standard methodologies in Python.

You Bring:

Masters degree in CS/Statistics/Data Science, with a specialization in machine learning.
Experience with Python, and ideally also Scala or Java.
Experience in developing ML models for structured data.
Proficient with Machine learning frameworks such as Tensorflow, PyTorch, Spark MLlib.
Industry experience in designing and implementing large-scale machine learning-based recommender systems.
Industry experience in A/B testing, experimentation design and test analysis.
Strong coding, machine learning, and statistical knowledge.

Preferred Qualifications:

Experience with Databricks, Snowflake, Spark, Tecton, Kubernetes, Helm, Jenkins.
Familiarity with standard methodologies in large-scale DL training/Inference.
Experience in cloud-based environments, such as AWS.
Experience working with custom ML platforms.
Experience with LLM applied in recommendation systems.
Proactive self-starter with experience working in fast-paced environments.

Mid-Level Machine Learning Engineer

\n\n

You Will:

\nDesign and develop various machine learning and deep learning models and systems for high-impact consumer-facing applications such as content personalizations and product recommendations.\n
\nWork with a broad spectrum of state-of-the-art machine learning and deep learning technologies in the areas of recommendation systems.\n
\nCreate metrics and design A/B test plans to evaluate model performance offline and online to inform and convey our impacts to diverse groups of stakeholders.\n
\nCollaborate with cross-functional teams of technical members and non-technical members in architecture, design, and code implementations.\n
\nAnalyze and produce insights from a large amount of dynamic structured and unstructured data using modern big data technologies.\n
Produce reusable code and conduct peer code reviews according to standard methodologies in Python.
Masters degree in CS/Statistics/Data Science, with a specialization in machine learning.
Experience with Python, and ideally also Scala or Java.
Experience in developing ML models for structured data.
Proficient with Machine learning frameworks such as Tensorflow, PyTorch, Spark MLlib.
Industry experience in designing and implementing large-scale machine learning-based recommender systems.
Industry experience in A/B testing, experimentation design and test analysis.
Strong coding, machine learning, and statistical knowledge.

You Bring:

\n\n

Preferred Qualifications:

Experience with Databricks, Snowflake, Spark, Tecton, Kubernetes, Helm, Jenkins.
Familiarity with standard methodologies in large-scale DL training/Inference.
Experience in cloud-based environments, such as AWS.
Experience working with custom ML platforms.
Experience with LLM applied in recommendation systems.
Proactive self-starter with experience working in fast-paced environments.

\n\n

Equal Opportunity Statement:

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy or parental, trade union membership or membership in any other legally protected category.

Equal Opportunity Statement:

Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.

We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.

PlayStation is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

\n","hiringOrganization":{"@type":"Organization","name":"PlayStation Global","sameAs":"https://www.playstation.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Ireland, Dublin","addressCountry":"Ireland","addressRegion":"Europe"}}}},{"@type":"ListItem","position":6,"item":{"@type":"JobPosting","title":"Machine Learning Engineer I","datePosted":"2025-09-19","description":"

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Job Duties: Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner while interfacing with various teams across Pinterest, Inc. Experiment with and improve machine learning models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search). Apply machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning). Build data processing pipelines, and work with large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark). Research machine learning applications across different areas. Use data driven methods and leverage the unique properties of Pinterest, Inc. data to improve candidates’ retrieval. Work in a high-impact environment with quick experimentation and product launches. Stay conversant with industry trends in recommendation systems. Telecommuting is permitted.

Minimum Requirements: Master’s degree (or its foreign degree equivalent) in Computer Science, Engineering (any field), or closely related quantitative discipline and one (1) year of experience in the job offered or in any occupation in related field.

Special Skill Requirements: (1) Data Structures; (2) Hadoop Distributed File System (HDFS); (3) Spark; (4) Machine Learning; (5) User Modeling; (6) Recommender Systems; (7) Search and ranking; (8) Natural Language Processing; (9) Scalable deep learning; and (10) Data Mining. Any suitable combination of education, training and/or experience is acceptable. Telecommuting is permitted.

Salary: $168,237.50 - $222,695.00 per annum
Reference #: L24-146887
This position is not available for relocation assistance.

\n\n

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only$168,237.50—$222,695 USD

Our Commitment To Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Know Your Rights and Pinterest Policy for more information regarding U.S. roles. If you require a medical or religious accommodation during the job application process, please complete this form for support.

","hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Remote, CA, US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":7,"item":{"@type":"JobPosting","title":"Sr. Machine Learning Engineer","datePosted":"2025-09-19","description":"

By making evidence the heart of security, we help customers stay ahead of ever-changing cyber-attacks.

Corelight is a cybersecurity company that transforms network and cloud activity into evidence. Evidence that elite defenders use to proactively hunt for threats, accelerate response to cyber incidents, gain complete network visibility and create powerful analytics using machine-learning and behavioral analysis tools. Easily deployed, and available in traditional and SaaS-based formats, Corelight is the fastest-growing Network Detection and Response (NDR) platform in the industry. And we are the only NDR platform that leverages the power of Open Source projects in addition to our own technology to deliver Intrusion Detection (IDS), Network Security Monitoring (NSM), and Smart PCAP solutions. We sell to some of the most sensitive, mission critical large enterprises and government agencies in the world.

We are building a world class and uniquely targeted team to drive research through data science and security expertise. The ideal candidate will use their strong analytic skills and awareness of network and cloud security data to drive novel, durable, and effective threat detection. Corelight can define the data our sensors generate, you will have the opportunity to contribute to how we extend the data itself to enable new types of analysis as
needed. You will be able to look back a year from now and say two things with pride: first, “I helped to build that.” and second, “We are generating insights that no one else in the world has achieved.”

As a Sr. Machine Learning Engineer within Corelight Labs, you will work closely with data scientists and network security experts to explore, design, build and deliver machine learning solutions for challenging network security problems. You will play a crucial role in the exploration and development of the ML capabilities powering our product offerings.

Responsibilities

Contribute to the full range of stages of AI/ML projects, from early explorations to productization and maintenance.
Work closely with data scientists and network security experts to design and implement scalable ML pipelines for large datasets.
Design and implement strategies to deploy LLMs and for fine-tuning.
Conduct experiments, analyze results and resource consumption using various metrics and visualization techniques.
Drive adoption of ML development best practices in code health, quality, test stability and maintainability.
Participate in technical discussions within the Labs team and collaborate with other teams across the organization.
Work in an Agile development team focused on exploring and delivering ML use cases.

Minimum Qualifications

Strong appreciation for our core values: low ego results, tireless service, and applied curiosity.
5+ years experience developing, optimizing, troubleshooting, and maintaining large-scale machine learning systems.
Experience in DevOps and/or MLOps: continuous integration and delivery, automation of ML workflows, and deployments to production environments.
Understanding of data preprocessing, feature engineering and machine learning algorithms.
Understanding of model testing and validation techniques for ensuring model quality and performance.
Proficient in Python and data science libraries (Pandas, Scikit-Learn, Keras, PyTorch, Tensorflow).
Experience using Docker and/or Kubernetes, and containerized applications.
Excellent communication skills to work effectively in a team.
Degree in Computer Science or related fields, or equivalent experience.

Preferred Qualifications

Experience adopting and using Agile development tools and methodologies, and working in a distributed team.
Experience with local deployments and fine-tuning of LLMs
Familiarity with the network security domain.
Experience using feature stores and ML frameworks like Kubeflow, Cortex, Seldon, or BentoML.
Experience in designing and implementing data pipelines using Apache Spark.
Experience with cloud computing, especially Databricks and AWS Services (EC2, S3, Cloudwatch)
Experience with experiment tracking and reproducibility tools.

We are proud of our culture and values - driving diversity of background and thought, low-ego results, applied curiosity and tireless service to our customers and community. Corelight is committed to a geographically dispersed yet connected employee base with employees working from home and office locations around the world. Fueled by an accelerating revenue stream, and investments from top-tier venture capital organizations such as Crowdstrike, Accel and Insight - we are rapidly expanding our team.

Check us out at www.corelight.com

Notice of Pay Transparency:
The compensation for this position may vary depending on factors such as your location, skills and experience. Depending on the nature and seniority of the role, a percentage of compensation may come in the form of a commission-based or discretionary bonus. Equity and additional benefits will also be awarded.

Compensation Range$203,000—$242,000 USD","hiringOrganization":{"@type":"Organization","name":"Corelight","sameAs":"https://corelight.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"North America"}}}},{"@type":"ListItem","position":8,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-19","description":"

About Definitive Healthcare:

At Definitive Healthcare (NASDAQ: DH), we’re passionate about turning data, analytics, and expertise into meaningful intelligence that helps our customers achieve success and shape the future of healthcare. We empower them to uncover the right markets, opportunities, and people—paving the way for smarter decisions and greater impact.

We’re headquartered in Framingham, Massachusetts, but we have 3 office locations globally, including locations in Sweden, and India. We’ve grown significantly since our founding in 2011 and have expanded our global client base to 2,400+.

We’re also a great place to work. In 2024, we brought home a number of awards including Built In’s 100 Best Places to Work in Boston, a Stevie Bronze Award for Great Employers, and we were recognized as a Great Place to Work in India.

We foster a collaborative, inclusive culture where diverse perspectives drive innovation. Through programs like DefinitiveCares and our employee-led affinity groups we strive to promote connection, education, and inclusion.

We are looking for a Senior Machine Learning Engineer to lead the design and implementation of cutting-edge AI/ML systems that deliver transformative business outcomes. In this role, you will take ownership of end-to-end ML solutions, from architecture and modeling to production and performance optimization.

From architecting end-to-end ML solutions to shaping technical strategy, your work will have a broad and lasting impact on customer experience and operational efficiency. The ideal candidate brings extensive experience in applied machine learning, deep software engineering expertise, and a track record of mentoring teams and delivering production-ready models at scale. This is a high-impact, full-stack ML role that blends research, engineering, and leadership, with the opportunity to shape both the company’s technical foundation and product direction.

Responsibilities:

ML Systems Development & Deployment

Lead the design and implementation of scalable, production-grade ML systems in cloud environments with a focus on performance, reliability, and reproducibility.
Collaborate with product managers and senior stakeholders to define and prioritize ML initiatives aligned with business goals.

Data Pipeline & Feature Engineering

Oversee the architecture and evolution of data pipelines for multi-terabyte datasets, ensuring efficiency and reliability.
Guide the development of high-impact features and label sets across diverse domains such as healthcare and consumer analytics

Experimentation & Model Management

Lead experimentation strategy, including design of A/B tests, advanced validation methods, and lifecycle management using tools like MLflow and Databricks.
Drive continual model improvement through advanced techniques such as automated retraining, model decay analysis, and bias mitigation. Innovation & Prototyping
Champion rapid prototyping and proof-of-concept development to evaluate emerging technologies and ML techniques.
Lead technical explorations into new ML architectures (e.g., foundation models, causal inference, time series deep learning).

Cross-Functional Collaboration

Serve as a technical leader and trusted advisor, working closely with product, engineering, data, and executive teams to shape end-to-end ML solutions. Code Quality & Documentation
Set standards for code quality, performance, and documentation, and mentor junior engineers in best practices

Required Qualifications:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
5+ years of industry experience as an ML Engineer, Data Scientist, or Data Engineer, with a focus on deploying and scaling ML systems.
Deep expertise in Python, SQL, and PySpark for distributed data processing, with proficiency in libraries like scikit-learn, PyTorch, and XGBoost.
Proven experience designing robust ML pipelines, leveraging tools like MLflow or equivalent.
Strong command of ML frameworks (e.g., scikit-learn, TensorFlow, XGBoost, PyTorch).
Hands-on experience deploying models in cloud-based environments (AWS, GCP, Azure, and Databricks).
Proven ability to manage end-to-end ML lifecycles at scale, including data ingestion, training, evaluation, deployment, and monitoring.
Excellent communication skills and demonstrated ability to influence cross-functional teams.

Preferred Qualifications:

Experience working with healthcare claims, EHR, or life sciences datasets.
Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or related technical field.
Strong knowledge of MLOps practices including CI/CD for ML, automated retraining, and model versioning.
Experience with deep learning architectures for time series forecasting, sequential data, or hierarchical modeling.
Proficient in designing evaluation protocols and defining performance metrics to rigorously assess model effectiveness and drive data-driven decision-making.
Comfortable operating in fast-paced, high-ownership environments, and able to prioritize multiple high-impact projects

Why we love Definitive, and why you will too!

Industry leading products
Work hard, and have fun doing it
Incredibly fast growth means limitless opportunity
Flexible and dynamic culture
Work alongside some of the most talented and dedicated teammates
Definitive Cares, our community service group, gives all of us a chance to give back
Competitive benefits package including great healthcare benefits and a 401(k) match

\n\n

What our Employees are saying about us on Glassdoor:

“Great Work atmosphere, great work life balance, excellent company to work for, amazing top notch product, incredible customer service, lots of tools to help you succeed.”

-Business Development Manager

“Great team. Amazing growth. Employees are treated very well.”

-Research Analyst

“I have waited 36 years to work at a dream job for a dream company and I am so happy to have finally got there.”

-Profile Analyst

\n\n

If you don’t fit all of these qualifications, but believe you’re still a great fit, feel free to apply and tell us why in your cover letter.

If you are a California, Colorado, New York City or Washington resident and this role is a remote role, you can receive additional information about the compensation and benefits for this role, which we will provide upon request.

\n\n

Definitive Hiring Philosophy

Definitive Healthcare is an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and teammates. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, religion, age, gender, gender identity, sexual orientation or any other status. If you’re interested in working in a fast growing, exciting working environment – we encourage you to apply!

\n\n

Privacy
Your privacy is important to us. Please review our Candidate Privacy Notice which tells you how we use and process your personal information.

\n\n

Please note: All communications regarding the hiring process at Definitive Healthcare will come directly from one of our corporate recruiters or coordinators with an @definitivehc.com email address. We will never request any money transfer or purchase of equipment with a promise of reimbursement. If you receive any suspicious communications, please reach out to careers@definfitivehc.com to confirm your status in the application process.

","hiringOrganization":{"@type":"Organization","name":"Definitive Healthcare","sameAs":"https://www.definitivehc.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":9,"item":{"@type":"JobPosting","title":"Sr. Machine Learning Engineer","datePosted":"2025-09-19","description":"

The opportunity
At Unity, we’re committed to building a culture grounded in Empathy, Respect, and Opportunity. Within our fast-paced and collaborative environment, we’re tackling complex challenges that drive meaningful impact for creators and users across our ecosystem. The Unity Demand Optimization team plays a central role in this effort by building ad campaign optimizations that enable advertisers to efficiently capture user engagement while minimizing their costs. The team leverages machine learning models to incorporate advertisers' off-site goals into auction ranking, helping them maximize installs, key conversions, or return on ad spend.

We are seeking a highly skilled staff engineer to take a critical role in building state-of-the-art bidding optimization systems that enable:

Efficient budget pacing across campaigns.
Automated bidding strategies that align with advertiser goals.
Continual system improvement through rigorous experimentation.
Sustainable growth for Unity’s advertising business.
What you'll be doing
Design, implement, and maintain high-performance auto-bidding algorithms and advertiser-facing products (e.g., Target ROAS, Target CPA).
Ensure these systems meet or exceed campaign performance goals, advertiser expectations, and system reliability standards.
Lead development on core initiatives such as:
A bid-based budget pacing system that ensures daily budget delivery.
Maximize Conversions, which leverages real-time bidding to meet key advertiser goals.
Lowest Cost, a product that automates bidding to simplify campaign management.
Target ROAS, which lets advertisers scale volume without sacrificing performance targets.
Drive best practices for model quality, experimentation, system reliability, and operational excellence.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

\n\n\n\n\n\n

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, or a related field—or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building control systems, PID controllers, multi-armed bandits, reinforcement learning algorithms, or bid/pricing optimization systems.
Significant experience in one or more general-purpose programming languages like Java, Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state of the art control systems, reinforcement learning algorithms.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

#Sen #Li-Ed1

\nGross pay salary$165,600—$248,600 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":10,"item":{"@type":"JobPosting","title":"Sr. Machine Learning Engineer","datePosted":"2025-09-19","description":"

We are seeking a highly skilled staff engineer to take a critical role in building state-of-the-art bidding optimization systems that enable:

Efficient budget pacing across campaigns.
Automated bidding strategies that align with advertiser goals.
Continual system improvement through rigorous experimentation.
Sustainable growth for Unity’s advertising business.
What you'll be doing
Design, implement, and maintain high-performance auto-bidding algorithms and advertiser-facing products (e.g., Target ROAS, Target CPA).
Ensure these systems meet or exceed campaign performance goals, advertiser expectations, and system reliability standards.
Lead development on core initiatives such as:
A bid-based budget pacing system that ensures daily budget delivery.
Maximize Conversions, which leverages real-time bidding to meet key advertiser goals.
Lowest Cost, a product that automates bidding to simplify campaign management.
Target ROAS, which lets advertisers scale volume without sacrificing performance targets.
Drive best practices for model quality, experimentation, system reliability, and operational excellence.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

\n\n\n\n\n\n

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, or a related field—or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building control systems, PID controllers, multi-armed bandits, reinforcement learning algorithms, or bid/pricing optimization systems.
Significant experience in one or more general-purpose programming languages like Java, Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state of the art control systems, reinforcement learning algorithms.

Additional Information

Relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ed1

\nGross pay salary$165,600—$248,400 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":11,"item":{"@type":"JobPosting","title":"Machine Learning Engineer l","datePosted":"2025-09-19","description":"

Opportunity Overview:

Our ML team’s work is focused on designing, deploying, and monitoring production models which extract or predict relevant clinical findings from structured and unstructured data sources.

In this role, you’ll join our growing team of world-class engineers, statisticians, and clinical experts to deploy machine learning algorithms that help automate burdensome administrative clinical practices. You will be tasked with finding the most promising opportunities for impact and then delivering on them. This is a unique opportunity to join a high caliber engineering team that is growing quickly. You will build impactful healthcare technology on a modern tech stack.

What You’Ll Do:

Perform in-depth analysis of healthcare data to independently design, develop, and deliver clinical ML models.
Build reliable and scalable production machine learning systems
Work on feature engineering, statistical analysis, developing novel ML techniques, understanding performance, and improving model run time.
Work cross-functionally across diverse stakeholders, including product managers, statisticians, clinicians, and clinical analysts.

What You’Ll Need:

You have 1+ years full time professional experience in ML
You have an MS in computer science, machine learning, computational linguistics, statistics, mathematics or similar field
You have hands on experience building with modern language models, including context-engineering LLMs or fine-tuning SLMs
You understand scientific best practice in experimental design and can independently perform data collection, measurement, and interpretation of results
You have experience configuring, training, evaluating, deploying, and maintaining models in a production setting
Advanced proficiency in Python and familiarity with ML frameworks such as PyTorch.

Bonus Points For:

Experience with healthcare data such as claims and EMR data
Experience with OCR
Experience with graph databases or network analysis
Hands on experience using AWS tools such as SageMaker Studio and Neptune

\n\n

Pay & Perks:

💻 Fully remote opportunity with about 5% travel

🩺 Medical, dental, vision, life, disability insurance, and Employee Assistance Program

📈 401K retirement plan with company match; flexible spending and health savings account

🏝️ Up to 184 hours (23 days) of PTO per year + company holidays

👶 Up to 14 weeks of paid parental leave

🐶 Pet Insurance

The salary range for this position is $95,000.00 to $110,000.00 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment.

\n\n

Interview Process*:

Connect with Talent Acquisition for a Preliminary Phone Screening
Meet your Hiring Manager!
Behavioral Interview(s)
Live Coding
Case Study

*Subject To Change

\n\n

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement:

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all. To us, it’s personal.

\n\n\n

#Li-Remote

#Bi-Remote

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Federato is on a mission to defend the right to efficient, equitable insurance for all. We enable insurers to provide affordable coverage to people and organizations facing the issues of today - the climate crisis, cyber-attacks, social inflation, etc. Our vision is understood and well funded by those behind Salesforce, Veeva, Zoom, Box, etc.

Federato’s AI/ML-driven platform leverages deep reinforcement learning to help insurance companies optimize the portfolio of risks they insure, allowing them to continue to provide fair and equitable pricing in difficult-to-price areas. Our category-defining ‘RiskOps’ solution drives better underwriting decisions by operationalizing underutilized data investments and surfacing real-time risk and portfolio insights. We focus on putting insurance underwriters back in the driver’s seat, helping them meet their goals while providing an important service to society.

What You'Ll Be Doing:

Design and implement scalable machine learning pipelines, serving prompt engineering workflows to enhance scalability and efficiency in submission intake processes across multiple insurance use cases.
Collaborate cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
Build reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
Champion best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.

Who We Hope You Are:

Proven experience as a Machine Learning Engineer or similar role (at least 5 years), with a strong focus on pipelining LLM models over the last 2 years.
Proven experience in designing scalable and robust machine learning pipelines, both for classical machine learning and large language models (LLMs) along with familiarity with open-source models is a plus.
Experience in building scalable ML pipelines using tools such as Kubeflow. Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
Great communication skills with the ability to convey complex findings to non-technical audiences.

\n\n

$180,000 - $220,000 a year
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks.

Here at Federato, your capabilities are important, but culture fit is quintessential. We move fast, are eager to listen to our users, take a first principles approach to solving problems, and value learning and the ability to change our minds. Most importantly, we're here to have fun. Our ability to make a difference starts with our people. We would love to work with you!

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender expression, sexual orientation, age, marital status, veteran status or disability status. We will provide reasonable accommodation to individuals with disabilities to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at talent@federato.ai

","hiringOrganization":{"@type":"Organization","name":"Federato","sameAs":"https://www.federato.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":13,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Applied Modeling (TakeUp)","datePosted":"2025-09-19","description":"

About Us

TakeUp, LLC is revolutionizing revenue optimization for hospitality with a daring approach to pricing. Using AI and machine learning, TakeUp empowers independent operators to unlock maximum revenue potential through pricing courageously—day in, day out. Seamlessly integrated with top Property Management Systems, our platform replaces traditional rate-setting constraints with data-driven confidence, delivering an impressive 10-15x ROI.

The Opportunity

We are hiring a Senior Machine Learning Engineer to focus on applied modeling for our rate optimization engine. This role is hands-on: designing, training, and deploying models that turn hotel data into reliable production outcomes. You will collaborate closely with the ML Engineering Manager, the CTO, and product partners to design modeling approaches, build pipelines, and support experiments that drive measurable revenue impact.

What You’Ll Do

Modeling

Design, train, and deploy production ML models, with emphasis on tree-based methods (XGBoost, LightGBM, CatBoost).
Contribute to feature engineering and model evaluation approaches that balance accuracy, interpretability, and speed.
Translate customer needs and product requirements into practical modeling tasks (classification, regression, ranking, uplift).
Develop custom performance metrics to evaluate models’ ability to generate reasonable counterfactual demand estimates while accounting for varying customer product expectations.
Support explainability efforts to justify rate decisions with clear artifacts and documentation.

Pipelines & Deployment

Build and maintain training and evaluation pipelines, ensuring offline metrics align with online business outcomes.
Partner with engineering to integrate models into production services and batch jobs with defined SLAs.
Contribute production ready Python and SQL code with strong testing and review practices.
Support data quality, observability, and reproducibility across the ML lifecycle.

Experimentation

Collaborate on experiment design, including A/B testing and staged rollouts.
Implement policy guardrails to ensure automated rate changes are safe and controlled.
Analyze experimental results, communicate lift and trade-offs, and document findings.

Collaboration

Work closely with product, engineering, and leadership to scope problems and propose modeling approaches.
Participate in code reviews, model reviews, and planning sessions.
Share learnings and contribute to improving team practices around modeling, metrics, and documentation.

Who You Are

4+ years of experience building and deploying ML models to production.
Proficiency in Python (scikit-learn, XGBoost/LightGBM/CatBoost).
Strong SQL skills and comfort with large, imperfect, real-world datasets.
Experience across the full model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.
Familiarity with experimentation design and metrics; able to reason about trade-offs and safeguards.
Clear communicator, comfortable working in a collaborative, fast-paced environment.

Nice To Have

Experience with causal inference (uplift modeling, causal forests, DML) or time-series modeling.
Exposure to reinforcement learning concepts (multi-armed bandits, dynamic programming, temporal-difference learning).
Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and dbt.
Familiarity with orchestration frameworks (Prefect, Airflow).
Familiarity with MLOps frameworks (Sagemaker, Vertex AI)
Domain knowledge in pricing, demand modeling, or hospitality.
Former start-up experience.

Why Takeup?

At TakeUp, we empower our team to innovate, grow, and succeed. You’ll join a passionate group of professionals who are committed to changing the way businesses run. This is mission-driven work: we’re empowering independent inns and small hotels, businesses often underserved and outgunned by enterprise competitors, with technology that levels the playing field.

Ready to take your career to the next level with a fast-growing SaaS company? Apply now and let's make an impact together!

Travel

This role is remote. While flexibility is key, we also value in-person connections. Travel may be needed for customer discovery, team building, and/or networking.

EQUAL OPPORTUNITY EMPLOYER
1848 Ventures celebrates diversity and is committed to inclusion. All qualified applicants receive consideration for employment without regard to race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, or status as a protected veteran.

","hiringOrganization":{"@type":"Organization","name":"1848 Ventures","sameAs":"https://www.1848ventures.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":14,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer- GenAI Platform","datePosted":"2025-09-19","description":"

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

The Opportunity:

We are looking for a versatile, curious, and energetic Senior Machine Learning Engineer to join our team of passionate and dedicated engineers. We are the backbone for Data Engineering and Machine Learning developments at Visa and we thrive on solving complex challenges on a global scale! As a Senior Machine Learning Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.

You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.

The Work Itself:

The Senior ML Engineer, as a part of our Generative AI team, will play a multifaceted role in the design, development, and deployment of our Large Language Model (LLM) applications. Key responsibilities will include creating applications based on the Retrieval-Augmented Generation (RAG) framework, developing efficient inferencing algorithms, and fine-tuning the LLM to cater to various applications.

This role will also involve leveraging various machine learning stacks to enhance system efficiency, researching new techniques to advance our LLM applications, and collaborating with cross-functional teams within the organization. In addition, the engineer will be responsible for documenting processes and workflows and sharing insights with the team.

This position requires a solid understanding of AI and machine learning principles, robust problem-solving skills, and the ability to thrive in a fast-paced, dynamic environment.

Essential Functions:

Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions.
Drive development effort End-to-End for on-time delivery of high quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards. Responsibilities span all phases of solution development including:
Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved
Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:
•2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)
Preferred Qualifications:
•3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
•Exposure to leading-edge areas such as Machine Learning, Big Data, Distributed Systems or SRE.
•Experience in at least one of the following: Python, Golang, Java, or C/C++
•Familiarity with web service standards and related patterns (REST, gRPC)
•Experience implementing solutions for low-latency, distributed services using open standard technologies.

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $130,700.00 to $184,440.00 to per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

","hiringOrganization":{"@type":"Organization","name":"Visa","sameAs":"https://visa.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin, TX, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":15,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"

Oddball believes that the best products are built when companies understand and value the things they are working on. We value learning and growth and the ability to make a big impact at a small company. We believe that we can make big changes happen and improve the daily lives of millions of people by bringing quality software to the federal space.

We are seeking a Machine Learning Engineer to design, implement, and maintain ML solutions that enable secure, scalable, and data-driven decision-making. You will work with large and complex datasets, collaborating with engineers and analysts to build and deploy models that deliver measurable impact.

What You’ll Be Doing

Develop, train, and deploy machine learning models using AWS SageMaker and related cloud-based services.
Design and maintain end-to-end ML pipelines for data ingestion, training, testing, deployment, and monitoring.
Collaborate with data engineers and data scientists to ensure datasets are clean, well-structured, and ready for modeling.
Implement monitoring, performance tuning, and retraining strategies for production models.
Document ML workflows, ensuring transparency and compliance with DHA policies.
Ensure all ML solutions adhere to federal security and privacy frameworks (HIPAA, NIST, CMMC, RMF).
Support cross-functional initiatives involving predictive analytics, automation, and healthcare decision support.

What You’Ll Bring:

3–5 years of experience as a Machine Learning Engineer, Data Scientist, or similar.
Strong hands-on experience with AWS SageMaker for model development and deployment.
Proficiency with Python and ML libraries such as scikit-learn, TensorFlow, or PyTorch.
Experience building and maintaining end-to-end ML workflows (training, evaluation, deployment, monitoring).
Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
Familiarity with ETL pipelines and working with large, structured/unstructured datasets.
Knowledge of cloud-based data environments and distributed computing (AWS, Spark, or similar).
Awareness of compliance requirements in healthcare/federal settings (HIPAA, NIST, RMF).
Performs other related duties as assigned.

Nice To Haves:

Experience with Databricks and Jupyter Notebooks for experimentation and prototyping.
Knowledge of MLOps practices (CI/CD for ML, model registries, monitoring frameworks).
Familiarity with data visualization tools (Tableau, Power BI, or similar).
Prior experience supporting DHA or federal healthcare data programs.

Requirements:

Applicants must be authorized to work in the United States. In alignment with federal contract requirements, certain roles may also require U.S. citizenship and the ability to obtain and maintain a federal background investigation and/or a security clearance.

Education:

Bachelor’s Degree

Benefits:

Fully remote
Tech & Education Stipend
Comprehensive Benefits Package
Company Match 401(k) plan
Flexible PTO, Paid Holidays

Oddball is an Equal Opportunity Employer and does not discriminate against applicants based on race, religion, color, disability, medical condition, legally protected genetic information, national origin, gender, sexual orientation, marital status, gender identity or expression, sex (including pregnancy, childbirth or related medical conditions), age, veteran status or other legally protected characteristics. Any applicant with a mental or physical disability who requires an accommodation during the application process should contact an Oddball HR representative to request such an accommodation by emailing hr@Oddball.io

Compensation:

At Oddball, it’s important each employee is compensated competitively and fairly. In alignment with state legal requirements. A range for the included position is listed below. Be advised, actual offer details are determined by job category, job location, and candidate skill level.

United States Wage Range: $115,000 – $160,000

","hiringOrganization":{"@type":"Organization","name":"Oddball","sameAs":"https://oddball.io/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":16,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, Recommendations","datePosted":"2025-09-19","description":"

Join Udemy. Help Define The Future Of Learning.

Udemy is an AI-powered skills acceleration platform built to help people and teams grow. It’s personalized, practical, and focused on real-world impact.

Our mission is simple: to transform lives through learning. Your work helps people around the world build skills they can use, whether they’re picking up something new or leveling up to stay ahead.

Over 80 million learners and 17,000 businesses already learn with Udemy. If you’re excited by change, energized by learning, and ready to have a real impact, you’ll feel right at home.

Learn more about us on our company page.

Where We Work

Udemy is a global company headquartered in San Francisco, with additional U.S. offices in Denver and Austin, and international hubs in Australia, India, Ireland, Mexico, and Türkiye. This is an in-office position, requiring three days a week in the office (Tuesday, Wednesday, Thursday) and flexibility on Mondays and Fridays.

\n\n

About This Role

Udemy is looking for a machine learning engineer to join our Recommendations Team. Udemy’s personalized recommendations system is composed of batch (e.g., feature and machine learning pipelines), streaming (i.e., feature computation in real-time), and online (i.e., microservices to serve personalized recommendations) components. The team is responsible for all these components, as well as the underlying algorithms and evaluation methodologies.

\n\n

In this role, you will design, build, and integrate scalable systems, platforms, and tools to provide better recommendations and personalization data with low latency. You will work in a wide stack, including both data-related technologies and backend development, as a part of a cross-functional agile team of engineers, data scientists, and product managers.

\n\n

Are you passionate about learning, willing to take technical challenges, care about making an impact, and looking for a diverse, collaborative, and fun environment that also values quality? If so, come help us improve lives through learning at Udemy!

\n\n

What you'll be doing

\nDesign, develop, test, and deploy recommendation- and personalization-related systems, platforms, and tools at scale.\n
\nDevelop performant ML models for realtime use-cases.\n
\nDesign and analyze experiments and monitor performance of personalized recommendations.\n
\nTranslate data science prototypes into scalable production implementations.\n
\nPartner with data scientists to troubleshoot and optimize complex data pipelines.\n
\nCollaborate with data scientists, engineers, and product managers to identify opportunities to improve our platform through personalization.\n

\n\n

What You'Ll Have

\n1-2 years of full-time experience with data science or backend engineering or equivalent.\n
Strong knowledge of computer science fundamentals, including object-oriented design, data structures, and algorithms.
Strong knowledge of statistics, machine learning, and natural language processing.
Proficiency with Python, Java and/or Kotlin.
Experience building complex data products.
Experience with offline data storage and processing frameworks such as Hadoop, Hive and Spark.
Self-driven, highly motivated, and able to learn quickly.
Excellent written and oral communication skills.
Preferred, but not required
\nExperience with the design, development, and operational maintenance of large-scale platforms and services.\n
\nExperience with recommendations, search or information retrieval.\n
\nExperience with online data storage and processing frameworks such as Kafka, MySQL, Redis, and DynamoDB.\n
\nExperience with SQL performance tuning and query optimization.\n

\n\n\n

At Udemy, we strive to be transparent around compensation. Actual compensation for this role is based on several factors, including but not limited to job-related skills, qualifications, experience, and specific work location due to differences in the cost of labor. In addition to a base salary, this role is also eligible for equity.

Hiring Compensation Range$140,000—$175,000 USD

Why Work Here?

You’ll grow here.
Learning is part of the job. You’ll get full access to Udemy courses, a monthly UDay to invest in yourself, and a budget to spend on whatever helps you improve. Many people are diving into AI lately, but what you focus on is up to you.

AI is real here.
We use it in the way we learn and the way we work. You’ll have the space and tools to experiment, apply, and get better at using AI in practical ways.
You’ll own your work.
We trust people to lead, make decisions, and follow through. You don’t need to wait for permission or layers of approval to have an impact.
You’ll build with others.
We collaborate openly and shape ideas together. Everyone has a voice, and good thinking is welcomed from any direction.
You’ll see your impact.
What you build helps people grow their skills, change their careers, or find a path forward. You’ve got the experience, why not use it to help others gain theirs?

\n\n\n\n

Bring your curiosity. We’ll bring the platform and the support. Let’s LEARN together.

Our Benefits Start With U

Our benefits start with you and were built to provide you and your family with the protection and care you need, making it easy to access the right coverage when you need it most. Benefits vary by region, and we encourage applicants to review our Australia Benefits, India Benefits, Ireland Benefits, Mexico Benefits, Turkiye Benefits & US Benefits, pages to get an understanding of some of the benefits we offer. For details on region-specific benefits, please refer to the information provided during the hiring process.

At Udemy, we value diversity and inclusion and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, or disability. We understand that not everyone will match each of the qualifications. However, we also realize that everyone has unique experiences that can add value to our company. Even if you think your background might not perfectly align, we'd love to hear from you!

\n\n\n\n\n\n\n\n\n

Information regarding data privacy is available within the Udemy Careers Privacy Notice.

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Join Udemy. Help Define The Future Of Learning.

Udemy is an AI-powered skills acceleration platform built to help people and teams grow. It’s personalized, practical, and focused on real-world impact.

Our mission is simple: to transform lives through learning. Your work helps people around the world build skills they can use, whether they’re picking up something new or leveling up to stay ahead.

Over 80 million learners and 17,000 businesses already learn with Udemy. If you’re excited by change, energized by learning, and ready to have a real impact, you’ll feel right at home.

Learn more about us on our company page.

Where We Work

\n\n

About This Role

\n\n

What you'll be doing

\nDesign, develop, test, and deploy recommendation- and personalization-related systems, platforms, and tools at scale.\n
\nDevelop performant ML models for realtime use-cases.\n
\nDesign and analyze experiments and monitor performance of personalized recommendations.\n
\nTranslate data science prototypes into scalable production implementations.\n
\nPartner with data scientists to troubleshoot and optimize complex data pipelines.\n
\nCollaborate with data scientists, engineers, and product managers to identify opportunities to improve our platform through personalization.\n

\n\n

What You'Ll Have

\n1-2 years of full-time experience with data science or backend engineering or equivalent.\n
Strong knowledge of computer science fundamentals, including object-oriented design, data structures, and algorithms.
Strong knowledge of statistics, machine learning, and natural language processing.
Proficiency with Python, Java and/or Kotlin.
Experience building complex data products.
Experience with offline data storage and processing frameworks such as Hadoop, Hive and Spark.
Self-driven, highly motivated, and able to learn quickly.
Excellent written and oral communication skills.
Preferred, but not required
\nExperience with the design, development, and operational maintenance of large-scale platforms and services.\n
\nExperience with recommendations, search or information retrieval.\n
\nExperience with online data storage and processing frameworks such as Kafka, MySQL, Redis, and DynamoDB.\n
\nExperience with SQL performance tuning and query optimization.\n

\n\n\n

Hiring Compensation Range$140,000—$175,000 USD

Why Work Here?

AI is real here.
We use it in the way we learn and the way we work. You’ll have the space and tools to experiment, apply, and get better at using AI in practical ways.
You’ll own your work.
We trust people to lead, make decisions, and follow through. You don’t need to wait for permission or layers of approval to have an impact.
You’ll build with others.
We collaborate openly and shape ideas together. Everyone has a voice, and good thinking is welcomed from any direction.
You’ll see your impact.
What you build helps people grow their skills, change their careers, or find a path forward. You’ve got the experience, why not use it to help others gain theirs?

\n\n\n\n

Bring your curiosity. We’ll bring the platform and the support. Let’s LEARN together.

Our Benefits Start With U

\n\n\n\n\n\n\n\nBenefits outlined are provided as a general overview and may vary depending on the location, role, and employment classification. All benefits are subject to change at the discretion of the organization and in accordance with applicable laws and policies.\n \nAt Udemy, we value diversity and inclusion and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, or disability. We understand that not everyone will match each of the qualifications. However, we also realize that everyone has unique experiences that can add value to our company. Even if you think your background might not perfectly align, we'd love to hear from you! \n\n\n\n\n\n\n\n

Information regarding data privacy is available within the Udemy Careers Privacy Notice.

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At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.

About Us

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.

Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.

In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.

At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The Role

We are seeking skilled engineers to join our Training Tech team working on optimising large scale training jobs as we aim to scale our models through the next order of magnitude. A successful candidate will increase efficiency of training jobs in order to allow Wayve to train larger models faster.

Key Responsibilities:

Profile training jobs to identify their bottlenecks, e.g. using NVIDIA Nsight Systems
Design and implement efficiency improvements to maximise MFU, e.g. tensor parallelism, model compilation, mixed precision
Design and implement observability tools, e.g. to track MFU
Collaborate closely with Research teams to integrate training efficiency improvements and create a culture of performance optimization

\n\n

About You

In order to set you up for success as a ML Engineer (Training Performance) at Wayve, we’re looking for the following skills and experience.

\n\n

Essential

Experience optimize large scale training jobs on GPU compute clusters.
Experience in working in platform teams and working with research teams.
Experience in reporting and tracking over time benchmarked performance in an open and accessible way.
Ability to write high quality, well-structured and tested Python code
BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

Desirable

Solid experience working with concurrent, parallel and distributed computing.
Experience using Nvidia NSight Systems.
Experience implementing GPU kernels.
Knowledge of computing fundamentals - what makes code fast, secure and reliable.

This is a full-time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.

We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

\n\n

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

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The Role

Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible.

Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.
As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales.
You will build foundational models for biology capable of reading and writing biology at scale
You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems
You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets
You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization
You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits

Who We'Re Looking For:

You have a Bachelor's in Computer Science, Machine Learning, or a related technical field
You have 3+ years of experience in developing and implementing deep generative learning models
You have experience pre-training models and are proficient in distributed computing environments
You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX)
You have experience with deep learning and generative architectures such as transformers, diffusion models and autoencoders
You are skilled in working with terra-scale datasets and scaling models to billions of parameters
You have a strong understanding of machine learning fundamentals, including various model architectures, optimization techniques, and evaluation metrics
You have experience in designing and implementing efficient data pipelines for processing and managing large datasets
You are experienced in developing robust evaluation frameworks and ensuring data integrity in machine learning projects
You are experienced in code organization, version control, and collaborative software development practices.

Who You Are:

You have excellent problem-solving skills and the ability to quickly adapt to new challenges
You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them
You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty
You have excellent communication skills and can clearly articulate complex technical concepts
You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity

Bonus Points

You have experience applying machine learning to biology or chemistry
You have contributed to open-source machine learning projects or published research papers in the field of AI/ML
You have experience optimizing machine learning models for high-performance computing environments
You are familiar with ML-Ops practices and tools for managing ML experiments and deployments

Our Values

❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions.

🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards.

🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of our patients and the broader community.

📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner.

🎮 Fun: We believe that life is too short to not have fun. That's why we're committed to creating an engaging and enjoyable work environment. Our goal is to create a workplace that is fun, rewarding and fulfilling.

What We Offer

We encourage new and different ideas, creativity and contrarian thinking.
You own your day-to-day management. What we care about is that we all hit our milestones.
Competitive salary and equity in a growing, well-funded startup
Excellent medical, dental, and vision coverage
Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you
We are looking forward to further shaping our culture with early team members. You'll have a chance to make your mark!

","hiringOrganization":{"@type":"Organization","name":"Output Biosciences","sameAs":"https://www.outputbio.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":20,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"

Your Turn To Start The Conversation.Write The Future At Rasa.

Conversation. It’s the thread between our product and our people. The tool that enables us to forge relationships through compassion and expertise. To find the connection between our differences. It keeps us close together across borders and backgrounds and helps us create our shared vision.

Rasa means tight-knit. We get to the point and have the courage to ask ‘why?’. Because through relentless experimentation, passion, and vision, we’re transforming the way people interact with organizations through AI.

That’s Rasa. That’s our message.

Join us and add yours.

Summary

We’re looking for a driven ML Engineer (mid-level) to join one of our cross-functional teams at Rasa. You will work closely with other engineers (ML, backend, full-stack) as well as a Product Manager and a Product Designer. Your mission will be to build our own rasa copilot which helps our users to efficiently build their Rasa assistant.

About This Role

Write code to enhance the Rasa Copilot and Rasa Pro codebase, both written using Python;
Design experiments, run them, analyse results and update on LLM prompts;
Contribute to the design and implementation of our evaluation system;
Work closely with the Product Manager and Product Designer to address shortcomings of the user experience as well as build new features;
Participate in engineering refinement sessions to seek clarity about your work and provide input;
Communicate proactively about your progress, blockers and ideas regularly in team meetings and huddles;

About The Team

This team has a Product Manager, a Product Designer, an hands-on EM, 1 backend engineer, 4 full-stack engineers, 1 ML engineer, 1 QA engineer. We currently work in Kanban, value proactive communication, iterative & data-driven product development, prototyping & POCs. The focus area of this team for the next 6 months is focusing on first-time user experience (onboarding) on the Rasa Platform. This team has a strategic impact and tightly coordinates with other squads in Rasa.

About You

Please keep in mind that we are describing the background we imagine would best fit the role. Even if you don’t meet all the requirements, yet you are passionate about this role: we absolutely want to get to know you!

You have 3+ years of experience building ML systems and features;
You’re familiar with modern LLM-based frameworks and protocols (e.g. MCP, A2A);
You have experience running experiments, trying different approach and follow clear evaluation protocols;
You both curious about machine learning and building commercial software that gets adopted;
You're comfortable being lean and fix problems without waiting for someone to tell you to;
You can effectively communicate what you’re working on within the team;

Please keep in mind that we are describing the background that would best fit the role. Even if you don’t meet all the requirements, yet you are confident that you are up for the task, we absolutely want to get to know you!

What You Can Expect From Us

Flexible hours and a dedicated remote budget
A stipend for professional development & 6 paid education days to help you grow within your role
Equity Options
26 days of PTO + paid sick leave + paid public holidays
A Macbook, and other tech to help you do your job
We have regular remote team events, as well as an annual company-wide offsite
Private Health optional (Serbia Only)
You can find more information about our benefits per location here: Rasa Perks & Benefits

About Us

Rasa is a leader in generative conversational AI, enabling enterprises to build and deliver next-level AI assistants. Merging a state-of-the-art engine with a user-friendly no-code UI, Rasa offers an open and adaptable platform that perfectly aligns with business logic. This innovative approach makes Rasa a reliable and trusted choice for enterprises seeking to enhance customer interactions while reducing costs. Rasa is privately held with funding from StepStone, PayPal, Accel, Andreessen Horowitz, Basis Set Ventures, and others. The company was founded in 2016 and is remote-first with a global presence.

Rasa is an equal opportunity employer. We are still a small team and are committed to growing inclusively. We want to augment our team with talented, compassionate people irrespective of race, color, religion, national origin, sex, physical or mental disability, or age.

Please Be Mindful Of The Hiring Location(S) Listed.

You must be located in and a resident of the location(s) listed for us to proceed with your application.

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Company Description

We are Nifty Coders Pvt. Ltd., a leading provider of Enterprise-Grade Software Engineering Services for startups and corporates. As experts in DevOps & Infrastructure, Application Development, and Service Reliability Engineering (SRE), we deliver innovative, reliable, and scalable solutions that drive business success and digital transformation.

Our commitment to excellence and industry best practices enables us to build high-quality, secure, and tailored software solutions that empower businesses to thrive. With a proven track record of successfully executing complex cloud migration and deployment automation projects, we are dedicated to helping our clients navigate the ever-evolving digital landscape, fostering long-term partnerships and growth.

Job Description

We are looking for a Senior ML Engineer to drive the development and deployment of scalable machine learning solutions. In this role, you will design, train, and optimize advanced models, build robust data pipelines, and collaborate with engineering and product teams to integrate AI capabilities into our systems. As a senior member of the team, you will establish best practices, mentor junior engineers, and lead initiatives that enhance automation, model reliability, and overall performance to deliver impactful, data-driven solutions.

Responsibilities:

Study, analyze, and transform business requirements into data science prototypes.
Design and implement machine learning systems using traditional ML algorithms (e.g., tree-based models, clustering), recommendation systems and transformer –based architectures.
Build, fine-tune, and deploy Large Language Models (LLMs), including local open-source LLMs (e.g., LLaMA, Mistral, Qwen) and API-based models.
Develop Generative AI applications, including Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., FAISS, ChromaDB, Milvus).
Run machine learning tests and experiments.
Train and retrain algorithms when necessary.
Extend existing ML libraries and frameworks.
Keep abreast of developments in the field.

Qualifications

Years of Experience: Minimum 5+ years of professional experience in software development, specializing in ML.
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

Requirements:

Proven experience as a Machine Learning Engineer or similar role
Understanding of data structures, data modeling and software architecture
Ability to write robust code in Python.
Hands-on experience with transformers and Hugging Face ecosystem.
Hands-on experience with Agentic frameworks like LangChain/LangGraph.
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Additional Information

Employment Type: Full-time
Weekend: 2 Days
Work Model: Hybrid

Compensation And Benefits:

Join a Workplace That Values You

At Nifty Coders Pvt. Ltd., we celebrate innovation, collaboration, and the unique contributions each of our employees brings. We prioritize a work environment that encourages growth, well-being, and a healthy work-life balance. Here, you’ll be part of a team that values creativity, promotes flexibility, and empowers individuals to thrive.

As part of our commitment to supporting you, we offer a range of benefits and perks designed to enhance your work experience:

Competitive compensation plans
Two annual bonuses
Paid Maternity Leave (4 months) and Paternity Leave (5 working days)
Comprehensive medical insurance for you and your dependents
Monthly and quarterly team-building events
Transport allowance
Mobile and internet allowance
Subsidized daily lunch
A dynamic performance review process that fosters ongoing transparency between managers and team members
Company-sponsored certifications programs for internal career growth and development

At Nifty Coders, we foster a culture of collaboration, continuous learning, and innovation, ensuring that every employee has the opportunity to grow and succeed.

Application Deadline: October 15, 2025

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The Role

Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.
As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales.
You will build foundational models for biology capable of reading and writing biology at scale
You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems
You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets
You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization
You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits

Who We'Re Looking For:

You have a Bachelor's in Computer Science, Machine Learning, or a related technical field
You have 3+ years of experience in developing and implementing deep generative learning models
You have experience pre-training models and are proficient in distributed computing environments
You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX)
You have experience with deep learning and generative architectures such as transformers, diffusion models and autoencoders
You are skilled in working with terra-scale datasets and scaling models to billions of parameters
You have a strong understanding of machine learning fundamentals, including various model architectures, optimization techniques, and evaluation metrics
You have experience in designing and implementing efficient data pipelines for processing and managing large datasets
You are experienced in developing robust evaluation frameworks and ensuring data integrity in machine learning projects
You are experienced in code organization, version control, and collaborative software development practices.

Who You Are:

You have excellent problem-solving skills and the ability to quickly adapt to new challenges
You exhibit a proactive approach to problem-solving, thinking beyond the specific task, taking ownership of challenges, and pride in solving them
You have a mature mindset in ambiguous situations, helping to frame questions and seek clarity while making decisions in the face of uncertainty
You have excellent communication skills and can clearly articulate complex technical concepts
You are motivated by making a real impact and are committed to tackling problems of significant consequence with determination and creativity

Bonus Points

You have experience applying machine learning to biology or chemistry
You have contributed to open-source machine learning projects or published research papers in the field of AI/ML
You have experience optimizing machine learning models for high-performance computing environments
You are familiar with ML-Ops practices and tools for managing ML experiments and deployments

Our Values

❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions.

🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards.

🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of our patients and the broader community.

📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner.

What We Offer

We encourage new and different ideas, creativity and contrarian thinking.
You own your day-to-day management. What we care about is that we all hit our milestones.
Competitive salary and equity in a growing, well-funded startup
Excellent medical, dental, and vision coverage
Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you
We are looking forward to further shaping our culture with early team members. You'll have a chance to make your mark!

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WHY JOIN US?

To work with a team of dynamic ML engineers and R&D team in a fast-growing start-up.
Contribute to KLAARA’s product development roadmap.
Identify and train suitable machine learning models to be used in conjunction with trading algorithms for complex problems.
Oversee the full ML model training lifecycle from data preprocessing to model serving.
Design and implement ML pipelines to allow for proper tracking of data trained models Deliver POC.
Progress within the state-of-the-art AI environment.
Fine-tune the current model and implement it.
Understand, analyse and define new models to create new use cases.
Lead a team of engineers.

Requirements

Ph.D or Master's Degree in Computer Science, Artificial Intelligence, Data Science is preferred.
Experience in ML model training/fine-tuning from Data preprocessing all the way to model serving.
Experience in optimising performance of ML models Experience with ML pipe lining tools.
Full proficiency in Python, R.
Understanding of basic Git commands.
Proficiency in Linux-based operating systems.
Strong knowledge in Machine Learning and Deep Learning (CNN, RNN, Random Forest, SVM, etc).
Experience with Document AI understanding, and extraction is a big plus.
Experience with Pytorch or Tensorflow.
Knowledge of DevOps CI/CD tools such as Jenkins.
Knowledge of container tools such as Docker and Kubernetes Github repository with projects is a big plus (we want to see what you have been able to create).
Ability to solve technical challenges and solutions.
Good command of spoken & written English and Mandarin.
A fast learner and able to work independently.

","hiringOrganization":{"@type":"Organization","name":"Upskills","sameAs":"https://www.upskills.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Raffles Quay, Singapore","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":24,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Graduate (Trust and Safety Platform)- 2026 Start (BS/MS)","datePosted":"2025-09-19","description":"About The Team
\nThe algorithm team is responsible for developing state-of-the-art computer vision, NLP and multimodality models and algorithms to protect our platform and users from the content and behaviors that violate community guidelines and related local regulations. With the continuous efforts from our team, TikTok is able to provide the best user experience and bring joy to everyone in the world.
\n
\nWe are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok
\n
\nSuccessful candidates must be able to commit to an onboarding date by end of year 2026. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
\n
\nWe are looking for a highly self-motivated research engineer to join our algo team. In our team, you will have the opportunity to participate in the development of the cutting-edge content understanding model to help improve the recognition ability of violated content in TikTok, and will also be responsible for optimizing our distributed model training framework continuously. The ideal candidate should be experienced in building a computer vision model or multimodality model and have a very strong coding ability in Pytorch/Tensorflow.
\n
\n1. Develop computer vision model or multimodality model to recognize violation content in TikTok
\n2. Explore cutting-edge multimodal or computer vision large models (CLIP, COCA, ALBEF, BLIP, Flamingo, ViT-G, ViT-22B, EVA-enormous, etc)
\n3. Explore the application of LLM in our business scenarios, like pre-training, zero-shot/ few-shot learning, hard case mining, etc
\n4. Continuously optimize the training framework to better adapt to the training of large models","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, Singapore","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":25,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, TikTok Vertical Search Intern - 2025 Start","datePosted":"2025-09-19","description":"About the team
\nOur Search Team is responsible for building and owning TikTok's search engine which provides our users the best search experience. On the TikTok Search Team, you’ll have the opportunity to build a full-stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
\n
\nCandidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.
\nApplications will be reviewed on a rolling basis - we encourage you to apply early.
\nSuccessful candidates must be able to commit to at least 3 months long internship period.
\n
\nResponsibilities
\n- Optimize the searching quality to provide TikTok's users the best search experience
\n- Combine your understanding of product objectives and take full advantage of modern machine learning, NLP and Multimodal techniques to improve the search ranking algorithms, including query understanding, video understanding and various levels of result ranking","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, Singapore","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":26,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, TikTok Search Local Services Intern - 2025 Start","datePosted":"2025-09-19","description":"About the team
\nOur Search Team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.
\n
\nCandidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally.
\n
\nApplications will be reviewed on a rolling basis - we encourage you to apply early.
\n
\nSuccessful candidates must be able to commit to at least 3 months long internship period.
\n
\nResponsibilities
\n- Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure;
\n- Improve the search experience in local services and promote ecosystem growth;
\n- Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences & Enhance conversion efficiency;
\n- Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation; CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.
\n- Utilize LLMs to understand users' complex local service search queries, summarize key points from numerous videos, comments, and POI reviews, and combine all those into structured AI search formats. Get involved in real-world AI applications, by building a revolutionized search experience for local service queries like destination choices, hotel searching, tourism, food & beverage reviews.","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, Singapore","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":27,"item":{"@type":"JobPosting","title":"Research Scientist Intern, Video Recommendations (PhD)","datePosted":"2025-09-19","description":"Meta is seeking AI Research interns to join our Video Recommendations team within Facebook. Videos (Reels, long videos, and Live streams) are increasingly the formats of choice across the social media industry, and making all these formats successful is a top priority for Facebook, and the core mission owned by this org. Time spent on Facebook watching videos accounts for 1.2+ Billion hours/day, which is over 56% of time spent globally on the App, and this number is expected to continue growing.

This team is directly in charge of recommending all sorts of videos to users. In this role, you'll be working primarily with Facebook's video content, which is predominantly driven by our recommendation system. Your job will involve optimizing our system to provide users with the most engaging and high-quality content. Our interns will have the opportunity to participate in the process of framing practical, high-impact challenges in recommendation into rigorous machine learning problems, and bring their own expertise to build innovative solutions under the guidance from our Research Scientists and Software Engineers.

More concretely, you will focus on solving end-to-end problems in the intersection of Product, ML and Infra, and serve as a bridge between high-demand business needs and long-term foundational investments via ML approach.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, Video Recommendations (PhD) Responsibilities

Perform research to advance the science and technology of intelligent machines
Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources
Analyze and improve efficiency, scalability, and stability of various deployed systems
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
Publish research results and contribute to research that can be applied to Meta product development
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field
Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
Experience with Python, C++, C, Java or other related language
Experience with deep learning frameworks such as Pytorch or Tensorflow
Familiarity with machine learning and common deep learning architectures
Intent to return to the degree program after the completion of the internship/co-op
Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP and KDD
Prior research or project experience in one or more of the following areas: reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, and their applications in recommendation systems
Demonstrated software development experience via tech internships, work experience, coding competitions, or widely used contributions in open source machine-learning repositories
Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results

Minimum QualificationsPreferred Qualifications For those who live in or expect to work from California if hired for this position, please click here for additional information. About Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
7.650 $/month to 12.134 $/month + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here. Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.

","hiringOrganization":{"@type":"Organization","name":"Meta","sameAs":"https://www.meta.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bellevue, WA | Menlo Park, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":28,"item":{"@type":"JobPosting","title":"Research Scientist Intern, Feed Recommendations (PhD)","datePosted":"2025-09-19","description":"Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.

Meta is seeking Research Interns to join our Feed Recommendation team within Facebook. This org is directly in charge of recommending all sorts of contents to users the time they open the app, and thus always gets the first-hand experience of critical pain points to solve. Our interns will have the opportunity to participate in the process of framing practical, high-impact challenges in recommendation into rigorous machine learning problems, and bring their own expertise to build innovative solutions under the guidance from our research scientists and software engineers.

More concretely, while the generative AI innovations in NLP are mainly focusing on optimizing the probabilities of selecting the next word token, in recommendation the vocabulary (contents to suggest) is at a much larger scale and also changing at a fast speed. The preference for these contents can also vary dramatically across users and time. If you’re excited about how to generate the correct sequences of “words” any time the giant number of Facebook users open or scroll down the blue app, come to join us!

Our internships are twelve (12) to sixteen (16), or twenty-four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, Feed Recommendations (PhD) Responsibilities

Perform research to advance the science and technology of intelligent machines
Develop novel and accurate NLP algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources
Analyze and improve efficiency, scalability, and stability of various deployed systems
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results
Publish research results and contribute to research that can be applied to Meta product development
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, Computer Vision, or relevant technical field
Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
Experience with Python, C++, C, Java or other related language
Experience with deep learning frameworks such as Pytorch or Tensorflow
Experience building systems based on machine learning, deep learning methods, or natural language processing
Familiarity with algorithms behind generative model training and common deep learning architectures (Transformers, GPTs, BERT etc.)
Intent to return to the degree program after the completion of the internship/co-op
Proven track record of solid research achievements as demonstrated by grants, fellowships, patents, as well as publications at leading AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP and KDD
Prior research or project experience in one or more of the following areas: reinforcement learning, pre-training and supervised fine-tuning of large language models, sequence modeling, diffusion models, and their applications in recommendation systems
Demonstrated software development experience via tech internships, work experience, coding competitions, or widely used contributions in open source machine-learning repositories
Experience working and communicating cross functionally in a fast-paced team environment. Ideal candidates should have the ability to quickly understand and identify the research opportunities behind real-world applications, select the appropriate ML methods to explore, and proactively drive the iterations based on clear analysis of the current results

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Team Overview:

Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.

What you get to do in this role:

Design, develop, and evaluate end-to-end machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.
Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
Conduct cutting-edge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.
Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.
Fine-tune and deploy large-scale models, incorporating prompt engineering, few-shot learning, and retrieval-augmented techniques.
Collaborate cross-functionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to open-source or peer-reviewed ML/AI research.
Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.
Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.
Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.

Qualifications

Key Qualifications:

Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
5+ years of experience in machine learning, deep learning, or data science, with a track record of applied research or experimentation.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
Hands-on experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
Proven experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.
Familiarity with data-centric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.
Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.
Practical experience deploying models using inference platforms like Triton, ONNX in production environments.
Experience working with MLOps stacks: CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
Excellent communication skills with the ability to explain complex ML ideas to non-technical stakeholders and contribute to scientific documentation.

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

","hiringOrganization":{"@type":"Organization","name":"ServiceNow","sameAs":"https://www.servicenow.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hyderabad, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":30,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-19","description":"Cherre is the real estate industry's leading data management platform, powering more than $3 trillion AUM globally. Our end-to-end platform helps clients connect, transform, analyze, and act on trusted data to increase efficiencies, reduce risks, gain visibility into market trends, and make strategic moves in response to changing market conditions.
We are looking to add a Machine Learning Engineer to our team. This role will be responsible for developing products that provide ML-powered insights to our customers and integrating those applications into the Cherre tech pipeline. Candidates must have an R&D / research background as well as industry-based engineering experience deploying models into production.
The work we do at Cherre touches multiple aspects of ML - the ideal candidate should be familiar with such diverse topics as deep learning, graph algorithms, and named entity resolution. Ability to implement algorithms at scale and experience with distributed computing / big data applications is critical - our knowledge graph has billions of edges!\n

Responsibilities

Work within an agile fullstack scrum team to deploy ML models into production
Develop new ML-based services that enhance our data capabilities
Design and implement scalable and repeatable ML pipelines
Collaborate with data engineering to design workflows for ingesting data streams required for ML applications

Requirements

2+ years software experience, preferably in an object-oriented language
3+ year experience deploying ML models in a production environment Industry-based experience with big data / distributed computing applications
Familiarity with current NLP technologies
Languages: Python, SQL
Technologies: Airflow, Kubernetes, Docker, GCP stack

Nice To Haves

Masters degree in Computer Science / Engineering discipline
Publications / patents in the field of machine learning
Technologies: Apache Spark

Starting Goals

30 Day
Familiar with the Cherre tech stack
Exposure to the Cherre release process
Understands company and team goals
Assigned a mini-project that they will own
60 Day
Familiar with the existing Cherre ML pipeline
Able to start contributing PRs
Understands the types of data we ingest and common customer use cases
90 Day
Contributing to the ML pipeline on a daily basis
Mini-project is completed

Benefits

Competitive Base Salary
Equity
Range of Healthcare Plans
Paid Parental Leave
Unlimited Vacation
Flexible Work Schedule
Compensation: $155,000-220,000/ year

If this opportunity sounds interesting, apply or reach out to our internal talent team. We are happy to tell you more about Cherre: the technology we work with, the problems we solve, the team we are assembling, and the culture we all contribute to. We are excited you are considering working with us and look forward to hearing from you!
“At the top of the mountain we are all snow leopards.” - Hunter S. Thompson
Cherre is an equal opportunity employer. We pride ourselves on hiring the best people for the job no matter their race, sex, orientation, nationality, religion, disability, or age.","hiringOrganization":{"@type":"Organization","name":"Cherre","sameAs":"https://cherre.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, New York","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":31,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"

Complyadvantage Technology

At Comply, we are building cutting-edge solutions that help prevent money flowing to and from bad actors to create a safer world. Your work will allow our customers to find out who is associated with crimes, financial and political risks, what that association is, and when it occurred, and it will dynamically update their state as new information emerges across a huge range of sources.

In our Entity Resolution Team we build and maintain data pipelines and services to perform Entity Resolution at scale. We use various ML and DS techniques to curate entities by ensuring their consistency and uniqueness across millions of data points. We define success via metrics representing our clients’ experience around minimising risk while also controlling operational costs.

What you will be doing

As a Machine Learning Engineer, you will

Build/train and productionize machine learning models for your squad
Build capabilities to monitor model performance and feature drift
Where appropriate re-use public models and techniques such as prompt engineering and RAG to reduce time to value
Collaborate with other software engineers in a cross functional team to design and implement intelligent services
Design software with scale, transparency and ease of operation in mind, writing maintainable, performant and well-tested code in Python
Integrate ML models into new and existing data pipelines to drive positive impacts for CA’s customers, including feature engineering as well as building APIs and consuming and producing event streams as inputs and outputs of models

Our Tech Stack:

Our technology stack is designed to run on public cloud architectures, notably AWS and GCP
We use Python and Kotlin in the backend and TypeScript, ES6 and React in the frontend
We make substantial use of modern database technologies (eg. Yugabyte) as well as Spark and cloud based object stores for big data processing
We also use an event-sourced model powered by Kafka for our communication bus and gRPC for our intra-service communication protocol
Our data and AI teams use a wide range of machine learning libraries, large scale hybrid columnar data stores such as Databricks, Spark for stream and big data processing in combination with Kafka, as well as some graph databases
We use modern observability solutions (Grafana) and deploy our code using ArgoCD

We have a strong emphasis on engineering excellence and strive to ship the best possible code and the best possible solutions to our customers.

About You:

Experience maintaining and scaling machine learning-powered applications in production environments.
Experience building scalable backend applications (preferably with Python).
A track record of working in multi-disciplinary teams alongside Data Scientists, ML Engineers, and Product Managers.
Hands-on experience with cloud platforms (AWS, Azure, or GCP) or with containerized infrastructure (e.g., Kubernetes, Docker, ArgoCD, Argo Workflows).
Strong communication skills and a collaborative mindset, with the ability to contribute to system design discussions and mentor more junior engineers.

Nice To Have:

Experience working with PySpark or other distributed data processing frameworks.
Background in building data-intensive applications or distributed systems using map-reduce style architectures.
Familiarity with event-driven or microservice architectures.

About ComplyAdvantage: We're a leading SaaS provider revolutionising how fintech companies navigate complex regulatory landscapes. Our platform powers compliance and risk management for hundreds of innovative financial services companies, from emerging startups to established enterprises. We believe in empowering our teams to solve meaningful problems and create exceptional value for our customers.

We have five global hubs in New York, London, Lisbon, Singapore and Cluj-Napoca.

Since 2014, we have raised over $100 million in funding and are backed by Goldman Sachs, Ontario Teachers, Index Ventures, Balderton Capital and a16z.

At ComplyAdvantage diversity fuels our growth and our commitment to inclusion across race, gender, age, religion, identity and experience drives us forward every day. We encourage everyone to apply and will consider every application fairly.

We will handle your information in accordance with our Privacy Policy. For further information, please click here.

","hiringOrganization":{"@type":"Organization","name":"ComplyAdvantage","sameAs":"https://complyadvantage.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Lisbon, Portugal","addressCountry":"Portugal","addressRegion":"Europe"}}}},{"@type":"ListItem","position":32,"item":{"@type":"JobPosting","title":"Senior Staff Machine Learning Engineer-Growth Marketing","datePosted":"2025-09-19","description":"

(Senior) Staff Machine Learning Engineer, Generative AI, Growth Marketing

About Growth Marketing ML

In Growth Marketing, our goal is to increase the number of transacting Customers while also growing their purchase frequency and lifetime value. We build core platforms and services that power Coupang’s growth, including Search Advertising, Affiliate Platform, Display Targeting & Re-targeting, CRM, Audience Platform, and other marketing services for landing, tracking & attribution.

Our ML team drives innovation across these platforms, including recommendation, personalization, budget optimization, keyword bidding, and creative optimization. We are now expanding into Large Language Models (LLMs) and Generative AI to transform how we optimize ads, creatives, and product recommendations at scale.

This is an exceptional opportunity to join a high-impact team and directly shape the future of LLM-powered growth marketing at Coupang.

\n\n

Basic Qualifications

8+ years of experience in ML engineering, including 2+ years hands-on with LLMs transformers, or generative models.
Demonstrated track record of owning ML projects end-to-end and driving measurable business impact.
Strong applied experience in training, fine-tuning, and deploying LLMs for real-world applications.
Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
Solid foundation in modern ML, including transformers, self-supervised learning, generative modeling, multimodal methods.

\n\n

Role & Responsibilities

Design and implement end-to-end LLM-driven solutions for advertising and marketing use cases (e.g., creative generation, product embeddings, recommendation, copywriting, targeting).
Develop and fine-tune large-scale transformer-based models (pretraining, instruction tuning, RAG, multimodal).
Build scalable pipelines for training, evaluation, and online serving of generative models.
Run experiments to measure business impact (CTR, CVR, GMV, ROAS) and iterate quickly.
Collaborate closely with cross-team members to integrate LLMs into production systems.
Mentor junior engineers and establish best practices for LLM/GenAI development.

Basic Qualifications

\n\n

8+ years of experience in ML engineering, including 2+ years hands-on with LLMs transformers, or generative models.
Demonstrated track record of owning ML projects end-to-end and driving measurable business impact.
Strong applied experience in training, fine-tuning, and deploying LLMs for real-world applications.
Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
Solid foundation in modern ML, including transformers, self-supervised learning, generative modeling, multimodal methods.
MS or PhD in Computer Science, Machine Learning, or related fields.

\n\n

Preferred Qualifications

Prior experience applying LLMs or generative AI in ads, recommendation, or creative optimization.
Experience building distributed training pipelines and scalable inference systems.
Familiarity with experimentation platforms and A/B testing at scale.
Strong cross-functional communication and ability to operate independently in a distributed global org.
Proven ability to mentor, influence, and set technical direction without formal management authority.
Strong written and verbal communication and teamwork skills.

\n\n

Recruitment Process and Others

\n\n

Recruitment Process

Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

\n\n

Details To Consider

This job posting may be closed prior to the stated end date for application if all openings are filled.
Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.

\n\n

Privacy Notice

Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/

\n","hiringOrganization":{"@type":"Organization","name":"Coupang","sameAs":"https://www.coupang.jobs/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Shanghai, China","addressCountry":"China","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":33,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"

Manulife is a leading international financial services provider, helping people make decisions easier and lives better. Help shape the future you want to see — and discover that better can take you anywhere you want to go.

JOB DESCRIPTION

People Leader Role: No

Responsibilities:

Support data operations lifecycle of AA projects - Input into the approach and Owns and manages assigned tasks.
Develops and implements ad-hoc and business analytics and reporting on projects of moderate scope
Own data pipeline and productionizing
Identify and gain access to sources of data with limited assistance from senior team members.
Work with internal and external team members to understand the data; present findings to the team.
Document the acquired data via standard team templates; present findings to the team
Create appropriate tables and DBs
Work with internal and external team members to code DS's solution in production system, coach junior team members.
Acquire data to measure effectiveness of the solution, present findings to internal and external peers, with guidance from senior team members.
Works on problems of moderate scope / complexity where analysis of situations or data requires a review of a variety of factors
Ability to generate relevant, actionable insights based on iterative data analysis, translate data-driven output into business language, and to make appropriate recommendations to respective business stakeholders
Strong ability to extract, transform and stage data for consumption by the data scientist leveraging data querying tools
Provides analysis on datasets of significant complexity.
Quickly able to develop enough business insight to connect data sources across multiple diverse and complicated systems.
Communicates business analytics of moderate complexity to more senior team members and junior business partners
Works closely with subject matter experts to understand data sources.
Has intimate understanding of the business value chain and customer lifecycle for the projects they are supporting.
Has fundamental understanding of the business as a whole.
Curious and asks the right kinds of questions of peers and customers to gain knowledge.
Establishes an internal network and leverages the network of more senior data analysts.
Provides guidance and mentorship to more junior team members Owns their career development.
Takes advantage of available resources to advance their technical and business skills.
Understands how their project supports broader business strategy, including the core drivers of business value

Some ability to construct systematic process to implement analytics insights and solutions, this includes (but not limited to):

designing a process with multiple relevant parties with clear specifications of roles and responsibilities
identifying required tasks, system / data flow and contingency
specifying check-and-balance throughout the process
establishing rigorous tracking and closed-loop learning
implement such process in a scalable way

Requirements:

Minimum Bachelor’s degree in Math, Computer Science, or Engineering; or Bachelor’s degree with equivalent technical experience
Minimum of 2 years of applicable experience Advanced knowledge of programming languages and concepts (g. Java, Sequel, C, SAS, SPSS, R (different modules) or Python)
Advanced knowledge of data visualization tools such as Tableau, QlikView, PowerBI
Advanced knowledge of data transformation to support BI Reporting Advanced knowledge of common database querying languages such as SQL.
Capability of applying a systematic, structured approach to explore / navigate / mine massive amount of data, structured or un-structured, to uncover hidden patterns / insights.
Strong working knowledge of relational database models ( data vaulting techniques, rules tables).
Advanced knowledge in distributed computing - Hadoop/ NoSQL/unstructured data
Basic understanding of different techniques and knowledge of machine learning algorithms.
Basic knowledge of AI toolkits.
Familiarity with basic statistical tests, distributions, maximum likelihood estimators, statistical modelling techniques (regression, cluster / factor / principle components, decision tree, survival analysis, etc.)

When You Join Our Team:

We’ll empower you to learn and grow the career you want.
We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
As part of our global team, we’ll support you in shaping the future you want to see.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit https://www.manulife.com/en/about/our-story.html.

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact recruitment@manulife.com.

Working Arrangement

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Support data operations lifecycle of AA projects - Input into the approach and Owns and manages assigned tasks.
Develops and implements ad-hoc and business analytics and reporting on projects of moderate scope
Own data pipeline and productionizing
Identify and gain access to sources of data with limited assistance from senior team members.
Work with internal and external team members to understand the data; present findings to the team.
Document the acquired data via standard team templates; present findings to the team
Create appropriate tables and DBs
Work with internal and external team members to code DS's solution in production system, coach junior team members.
Acquire data to measure effectiveness of the solution, present findings to internal and external peers, with guidance from senior team members.
Works on problems of moderate scope / complexity where analysis of situations or data requires a review of a variety of factors
Ability to generate relevant, actionable insights based on iterative data analysis, translate data-driven output into business language, and to make appropriate recommendations to respective business stakeholders
Strong ability to extract, transform and stage data for consumption by the data scientist leveraging data querying tools
Provides analysis on datasets of significant complexity.
Quickly able to develop enough business insight to connect data sources across multiple diverse and complicated systems.
Communicates business analytics of moderate complexity to more senior team members and junior business partners
Works closely with subject matter experts to understand data sources.
Has intimate understanding of the business value chain and customer lifecycle for the projects they are supporting.
Has fundamental understanding of the business as a whole.
Curious and asks the right kinds of questions of peers and customers to gain knowledge.
Establishes an internal network and leverages the network of more senior data analysts.
Provides guidance and mentorship to more junior team members Owns their career development.
Takes advantage of available resources to advance their technical and business skills.
Understands how their project supports broader business strategy, including the core drivers of business value

Some ability to construct systematic process to implement analytics insights and solutions, this includes (but not limited to):

designing a process with multiple relevant parties with clear specifications of roles and responsibilities
identifying required tasks, system / data flow and contingency
specifying check-and-balance throughout the process
establishing rigorous tracking and closed-loop learning
implement such process in a scalable way

Requirements:

Minimum Bachelor’s degree in Math, Computer Science, or Engineering; or Bachelor’s degree with equivalent technical experience
Minimum of 2 years of applicable experience Advanced knowledge of programming languages and concepts (g. Java, Sequel, C, SAS, SPSS, R (different modules) or Python)
Advanced knowledge of data visualization tools such as Tableau, QlikView, PowerBI
Advanced knowledge of data transformation to support BI Reporting Advanced knowledge of common database querying languages such as SQL.
Capability of applying a systematic, structured approach to explore / navigate / mine massive amount of data, structured or un-structured, to uncover hidden patterns / insights.
Strong working knowledge of relational database models ( data vaulting techniques, rules tables).
Advanced knowledge in distributed computing - Hadoop/ NoSQL/unstructured data
Basic understanding of different techniques and knowledge of machine learning algorithms.
Basic knowledge of AI toolkits.
Familiarity with basic statistical tests, distributions, maximum likelihood estimators, statistical modelling techniques (regression, cluster / factor / principle components, decision tree, survival analysis, etc.)

We’ll empower you to learn and grow the career you want.
We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
As part of our global team, we’ll support you in shaping the future you want to see.

About Manulife and John Hancock

Manulife is an Equal Opportunity Employer

Working Arrangement

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Looking for a new challenge?

Take a look at our current vacancies. If you see a vacancy that is right for you, we encourage you to apply!

Machine Learning Engineer

We’re looking for a passionate and skilled Machine Learning Engineer who’s excited by the opportunity to build real-world solutions that make a genuine difference. If you thrive in a collaborative environment, enjoy solving complex problems with data, and want your work to have a direct and visible impact — this could be the perfect next step in your career.

Contract: Permanent

Salary: London - Circa £70,000 (DOE) Manchester – Circa £62,000 (DOE)

Working hours: 35 hours per week, full-time

Reporting to: Machine Learning Lead

Location: London Docklands or Manchester City – Our permanent hybrid policy sees us all working at least four days across a fortnight in the office.

At the Financial Ombudsman Service, we’re on an exciting journey to redefine what modern, efficient, and accessible alternative dispute resolution looks like. Our mission? To set the gold standard for customer-focused service in a rapidly evolving financial landscape.

Over the past few years, we’ve embraced bold changes to enhance the customer experience and strengthen our financial sustainability. With a newly formed Executive team at the helm, we’re entering a transformative new chapter—driven by ambition, innovation, and a commitment to moving fast and delivering real impact.

Our Intelligent Automation team is at the heart of this transformation. We’re harnessing the power of AI and Generative AI to unlock smarter, faster, and more scalable solutions across the business.

We’re looking for someone with a proven track record in developing and deploying machine learning solutions—someone who’s ready to take our NLP and Gen AI capabilities to the next level. In this role, you’ll be:

Designing and building Gen AI application stacks
Scaling and maintaining ML pipelines and data transformation workflows
Driving ML Ops excellence across the board

You’ll collaborate closely with architects, senior developers, product owners, and analysts—shaping requirements, influencing solution design, and contributing to architectural decisions. You’ll play a key role in sprint planning, owning user stories, and estimating work that directly impacts our business teams.

This is more than just a technical role—it’s a chance to solve real-world problems using data, automation, and AI. You’ll work hand-in-hand with stakeholders across the organisation, sharing your expertise, building documentation, and helping shape the future of intelligent automation at the Service.

Key Responsibilities

Assess and clarify requirements to provide estimate of the work.
Working within a distributed team, delivering high quality solution
Delivering LLM and Gen AI based automations that supports the business team in enhancing the customer journey
Maintaining our existing machine learning pipelines
Identifying opportunities for Continuous Improvement and optimizations of existing solutions
Input to overall sprint planning and product backlog creation/maintenance.

To be considered for this role, you’ll need to show us that you’ve got the skills and capabilities. You’ll have to meet the following minimum criteria:

Minimum Criteria

Solid programming experience in Python, as well as solid understanding of programming concepts, algorithms and cloud concepts
Previous experience in solution design and knowledge of architecture frameworks and patterns
Developing serverless pipelines in Azure, AWS or GCP (Azure preferred) and building data transformation pipelines using SQL and No SQL DB
Building and maintaining CI/CD pipeline in Jenkins, Azure DevOps or GitHub actions and ML Ops pipeline in Azure ML, Azure AI Foundry, SageMaker or Vertex AI. IaC – Bicep, ARM, Terraform
Have a good understanding of different machine learning techniques and ability to explain the methods in detail (regression, clustering, decision trees, reinforcement learning, gradient boosting, CNN, RNN, LSTM, Attention Models, Encoder and Decoder, Transformers, Vector semantics)
Previous experience in developing Gen AI applications.
Ability to communicate technical concepts and analytical outputs to a diverse set of stakeholders.
Being able to provide estimates against organisational requirements relating to cost and development tasks

Tech Stack

Azure Data Factory, Logic Apps
Sql, Cosmos Db
Azure Batch, Azure Functions
Azure Dev Ops – CI/CD, Bicep templates
Azure AI services – Azure AI Foundry, Azure ML, Azure Open AI, Azure Doc Intelligence, Azure Speech to Text
Copilot Studio, D365, M365 Copilot
Python, C#

Why Financial Ombudsman Service?

We are a values led organisation. Our values define our culture, influence our decisions, and underpin our vision and strategy. They set out how we play our PART through Purpose, Ambition, Respect and Trust. You can learn more about our values here: https://www.financial-ombudsman.org.uk/who-we-are/aims-values

We also offer an attractive, competitive salary and flexible benefits to suit our people. Here’s a list of some of the many benefits and perks you can get for working with us:

25 days holiday entitlement, with the option to buy extra or sell days
Generous Pension
Various Family Friendly Policies, including enhanced maternity pay, carers and dependants leave
Employer provided benefits such as Private medical insurance, virtual GP, Critical illness cover, Life assurance cover, to name a few
Choice of voluntary benefits including Technology scheme, Cycle to work scheme, Will-writing service amongst others
Employee Assistance Programme
Extensive opportunities for personal and career development
Nationwide gym membership discounts, and a fully equipped on-site gym open 24/7 in London
Extensive Well-being resources including on-site therapists (London office only)
Beautiful and bright London office looking over the Thames and near to mainline stations
Our Manchester office is 7 minutes’ walk from the Oxford Road station
Our employee led networks (a couple of examples being our Women's Network, Carers network, and Neurodiverse Network) do fantastic work in educating and raising awareness across a range of experiences and support us in being an inclusive employer and a great place to work. You can get involved, too!

How do I apply?

Please upload your CV, which should highlight your relevant skills and experience.

This advert will close at Midnight on Sunday, 5th October 2025

Due to high application numbers this advert may end earlier than the date specified, so please don't delay and submit your application asap.

A full job profile is available on request and will be provided to candidates shortlisted to the first stage of the recruitment process.

We’re proud to be an inclusive employer

We view diversity as fundamental to our success and welcome applications from underrepresented groups across all communities.

We’re committed to being a great place to work– attracting and developing people from the widest possible range of backgrounds. We want everyone to perform at their best and feel able to be themselves. We understand that if we’re diverse and inclusive, we’ll better understand different perspectives, which is fundamental to our job resolving financial complaints.

We welcome applications from Black and other ethnic minority candidates, and female candidates, for all positions and particularly so for senior leader positions as they are under-represented within the Financial Ombudsman Service at this level.

We are proud to be a Disability Confident Leader. This means that we will put disabled candidates entering under the scheme through to the next stage of the recruitment process should they meet the minimum criteria for a role. A minimum criterion needs to be measurable from reviewing a candidate’s CV/supporting statement. Exceptions may apply if due to the volume of applications, we are not able to interview all eligible candidates who qualify under the scheme. If you would like to speak to a member of our team about any reasonable adjustments you need, please email hrsupport@financial-ombudsman.org.uk and let us know your preferred method of contact.

Find Out More

Check out below channels to find out more about everyday life at the Financial Ombudsman Service – and don’t forget to follow us while you’re there!

LinkedIn: Financial Ombudsman Service
Our careers page: https://www.financial-ombudsman.org.uk/who-we-are/join-us
Good luck with your application!

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At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

GEICO is seeking an experienced Sr Staff Machine Learning Engineer – Agent Engineering to join our AI org. This person will play key roles for the development of Geico’s virtual assistant platform that elevates the productivity for 30K+ internal associates and the customer experience for millions of our policyholders. You will be collaborating with a dynamic team of AI and software engineers to design, develop and deploy systems that ensure productivity, scalability and usability of GenAI workflows across Geico. Agent Engineers implements GenAI solutions for business stakeholders with both proven capabilities and experimental features, while synthesizing valuable insights to influence the product roadmap of the platform. The ideal candidate should demonstrate a proven track record of building high performance AI solutions, with hands-on experience in Generative AI-related ecosystems.

Responsibilities:

Own design, development and maintenance of high-performance AI solutions that utilize agentic workflows to deliver concrete business value for internal stakeholders. Examples include knowledge assistants, document processing copilots, voice agents, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Contribute to the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Take ownership in project planning and stakeholder management, ensuring the efficient allocation of resources and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture.

Basic Qualifications

10+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python, TypeScript, etc..
7+ years of experience architecting, building & deploying end-to-end AI solutions utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. Cassandra), distributed processing (e.g. Spark, Ray), workflow orchestration (e.g. Airflow, Temporal), etc. Balance craft, ownership, and speed.
5+ years’ experience managing end-to-end solution development life cycle, esp. Measurement and monitoring of operations metrics, analytical insights and business outcomes via dashboards and other tools.
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

5+ years’ experience interfacing directly with internal business stakeholders and/or external stakeholders on AIML initiatives
4+ years’ experience with tools that power LLM-based AI agents: eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc.
3+ years’ experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Strong communication and problem-solving skills to excel in dynamic, cross-functional and ambiguous decision-making environments

Annual Salary

$130,000.00 - $300,000.00

The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

Great Company: At GEICO, we help our customers through life’s twists and turns. Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.

We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success. From day one, you’ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people’s lives.

Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career – and your potential – in mind. You’ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.

Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"NY Manhattan (Office) - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":37,"item":{"@type":"JobPosting","title":"Sr Machine Learning Engineer","datePosted":"2025-09-19","description":"

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Job Description:

Essential Responsibilities:

Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

MSc or equivalent experience in a quantitative field (Computer Science, Mathematics, Engineering, Artificial Intelligence, etc.) or a bachelor's degree in engineering, science, statistics or mathematics with a strong technical background in machine learning.
Hands-on experience with Python or Java, along with relevant technologies such as Spark, Hadoop, Big-Query, SQL, is required. 
Candidates must possess a comprehensive understanding of machine learning algorithms and explainable AI techniques. Additionally, expertise in at least one of the following specialized areas is required: Computer Vision, Graph Mining, Natural Language Processing (NLP), or Generative AI (GenAI).
Experience with Cloud frameworks such as GCP, AWS is preferred.  
Experience with developing machine learning models at scale from inception to business impact
Experience in designing ML pipelines, including model versioning, model deployment, model testing, and monitoring
Experience in mentoring and supporting junior data scientists or engineers.
Experience working in a multi-cultural and multi-location organization – an advantage.
Team player, responsible, delivery-oriented, details-oriented, outstanding communication skills.

Subsidiary:

PayPal

Travel Percent:

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com.

Who We Are:

Click Here to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Belonging At Paypal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

","hiringOrganization":{"@type":"Organization","name":"PayPal","sameAs":"https://www.paypal.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IRL - County Dublin - Dublin - Corp - Ballycoolin Business Park, Ireland","addressCountry":"Ireland","addressRegion":"Europe"}}}},{"@type":"ListItem","position":38,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

About Us

Automation Anywhere is the leader in Agentic Process Automation (APA), transforming how work gets done with AI-powered automation. Its APA system, built on the industry’s first Process Reasoning Engine (PRE) and specialized AI agents, combines process discovery, RPA, end-to-end orchestration, document processing, and analytics—all delivered with enterprise-grade security and governance. Guided by its vision to fuel the future of work, Automation Anywhere helps organizations worldwide boost productivity, accelerate growth, and unleash human potential.

Staff Engineer – Machine Learning

Job Description

We are seeking a highly skilled Staff Machine Learning Engineer with a strong background in Machine Learning and Software Engineering to join our team. In this role, you will collaborate closely with product managers, applied scientists, and engineers to design, implement, and scale ML-powered systems that extract and reason over information from complex, unstructured data sources—such as documents, web screens, and automation workflows. Your work will play a key role in enabling intelligent, context-aware assistants and task automation agents that understand user intent and deliver meaningful outcomes.

Key Responsibilities

Build intelligent agentic systems that combine document understanding, retrieval, and LLM-based reasoning to support context-aware conversational workflows.
Design and implement scalable Agentic RAG pipelines that orchestrate unstructured data preprocessing, vector store integration, and LLM prompting for accurate, grounded responses.
Develop modular ML components for layout analysis, information extraction, dialogue management, and tool invocation within multi-turn, goal-driven conversations.
Integrate conversational agents with enterprise data sources, APIs, and downstream automation workflows to enable end-to-end task execution.
Craft dynamic prompting and memory strategies to maintain context, reduce hallucination, and improve relevance in long-form or multi-turn queries.
Collaborate cross-functionally with product managers, UX designers, and platform engineers to define agent behavior and ensure seamless user experiences.
Monitor and continuously improve system performance, including response quality, retrieval precision, latency, and task success rate using real-world feedback.
Drive data curation efforts including synthetic generation, annotation workflows, and hard example mining to improve agent robustness and generalization.
Establish best practices for evaluating agent behavior, including human-in-the-loop review processes, regression testing, and safety guardrails.
Contribute to infrastructure and MLOps pipelines that support model experimentation, deployment, and monitoring in production environments.

Qualifications / Expectations:

Bachelor’s or Master’s Degree in Computer Science, Data Science, or a related technical field. Advanced degrees are a plus.
5–7+ years of hands-on experience in building and deploying machine learning models, with a strong focus on document intelligence, NLP, or Generative AI.
Proven experience developing and productionizing ML systems for unstructured data processing, including document parsing, table extraction, and layout analysis.
Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and experience with OCR and document processing tools (e.g., Tesseract, AWS Textract, PDFMiner, LayoutParser).
Strong experience with LLMs and Retrieval-Augmented Generation (RAG) architectures, including practical knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks.
Experience building ML pipelines and implementing MLOps best practices to support training, validation, deployment, and monitoring of models at scale.
Hands-on experience with cloud ML services (e.g., AWS SageMaker, Azure ML, Google Vertex AI) for training and inference.
Solid programming skills in Python, with working knowledge of SQL
Experience with containerization (Docker), orchestration (Kubernetes), and model serving technologies (e.g., Triton Inference Server, ONNX Runtime, TorchServe) in production environments.
Knowledge of model optimization techniques (e.g., quantization, pruning, distillation) to improve inference efficiency on cloud or edge devices.
Strong problem-solving abilities, with a track record of delivering scalable, high-impact ML solutions for complex, real-world problems.
Excellent communication skills and ability to work autonomously in a fast-paced, collaborative environment.
Understanding on knowledge graphs and graph based information retrieval
Experience designing and integrating conversational agents with context memory, function/tool calling, and dynamic prompting strategies.
Familiarity with vector stores (e.g., FAISS, Pinecone, Weaviate) and search/retrieval mechanisms for grounding LLM outputs.

Nice To Have:

Experience in fine-tuning large language models (LLMs) and applying GenAI techniques in parsing unstructured data.
Experience with dialogue management systems or conversational frameworks (e.g., Rasa, Dialogflow, or custom pipelines) for building intelligent agents.
Experience with distributed training techniques to optimize large-scale model training across multiple GPUs or cloud environments.
Understanding of prompt engineering best practices and few-shot or chain-of-thought prompting for improving agent behavior in GenAI systems.
Background in open-source contributions or research related to document AI, LLM applications, or multi-modal learning.
Familiarity with CI/CD pipelines for ML, automated model versioning, and monitoring tools for performance and drift in production models.

All unsolicited resumes submitted to any @automationanywhere.com email address, whether submitted by an individual or by an agency, will not be eligible for an agency fee.

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At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

GEICO is seeking an experienced Sr ML engineer to join our AI org. This person will play key roles for the development of Geico’s virtual assistant platform that elevates the productivity for 30K+ internal associates and the customer experience for millions of policyholders. You will be collaborating with a dynamic team of AI and software engineers to design, develop and deploy systems that ensure productivity, scalability and usability of GenAI workflows across Geico. AI Agent Platform Engineers are responsible for building key multi-tenant services that power the building, testing, simulation, deployment and hosting of LLM-based agents. The ideal candidate should demonstrate a proven track record of building high performance AI/ML platform & systems, with hands-on experience and deep enthusiasm for Generative AI and related ecosystems.

Responsibilities:

Own design, development and maintenance of high-performance, durable and scalable platform components that jointly power large sets of end-to-end GenAI agentic workflows. Examples include AI agent building & deployment, prompt management, workflow orchestration, MCP registry, etc.
Contribute to the selection, evaluation, and implementation of software platforms, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Basic Qualifications

5+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python or C#.
4+ years of experience designing and building AIML platform and systems utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. MongoDB, Cassandra), distributed processing (e.g. Spark, Ray), workflow management (e.g. Airflow, Temporal), memory management (e.g. Redis), etc.
3+ years’ experience managing end-to-end software development life cycle (version control, CICD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support etc.)
3+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

3+ years’ experience with cloud providers such as Azure and AWS
2+ years’ experience building conversational experiences and agentic workflows, leveraging open source LLMs, e.g. Llama, Mistral, Claude etc.
Experience with LLM observability software such as Langsmith, Arize Phoenix, etc.
Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments

Annual Salary

$115,000.00 - $230,000.00

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"CA Palo Alto - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":40,"item":{"@type":"JobPosting","title":"Data Scientist/Machine Learning Engineer","datePosted":"2025-09-19","description":"

Data Scientist/Machine Learning Engineer

AI for Healthcare Data Science Team, Real World Solutions

Iqvia™

The IQVIA “AI for Healthcare” Data Science team is one of the leading healthcare analytical teams in the world. Joining provides the opportunity to work with extremely complex data and methodologies in a fast-paced, ever-changing environment. We seek highly motivated people who truly want to make a difference in the life sciences industry. At IQVIA, we look for the very best people and then give them meaningful work to do. We don’t simply think about careers, we think about contributions.

About IQVIA
IQVIA™ is the leading human data science company focused on helping healthcare clients find unparalleled insights and better solutions for patients. Formed through the merger of IMS Health and Quintiles, IQVIA offers a broad range of solutions that harness the power of healthcare data, domain expertise, transformative technology, and advanced analytics to drive healthcare forward.

Role Overview
We are looking for an innovative, collaborative, intellectually curious and entrepreneurial AI Engineer / Data Scientist to join our Healthcare Data Science team based in Philadelphia (King of Prussia). This is an exciting opportunity to join a fast-moving start-up style group within one of the world's leading human data science companies.

The primary focus of the role is to develop novel healthcare ML solutions on highly complex, large-scale medical data, and deploy production-grade solutions into a range of internal and external production environments to deliver patient-level alerts to healthcare providers across the world. The role requires close coordination and collaboration with our broader Data Science team (located across the UK and India), and with Consultants in our US team.

A Typical Day Might Include:

Working with the team and client to shape and develop requirements for answering ambitious life science questions (e.g. can we predict a rare disease diagnosis or an optimal dosing frequency in patients?) along with solutions for applying predictive analytics methods within infrastructures specific to each healthcare provider project.
Addressing those requirements by developing and applying appropriate ETL processes (for cohort and feature creation from the raw data) and machine learning methodology (for constructing predictive models in an unbiased manner).
Working with clients and engineering teams to plan and execute technical handovers of our algorithms to deliver alerts to the client’s healthcare providers.
Communicating technical concepts and analytical outputs to a diverse set of stakeholders (internal and external).
Proactively identifying opportunities for innovation and areas for improvement across our project workflow.
Researching machine learning techniques that could be used to improve our offering.

Ideally You Will Have:

One Of The Following:

A PhD in a technical or scientific domainOR
A technical/scientific MSc plus at least two years of experience working in a technical/consulting environment involving machine learning, preferably in a commercial setting.

Additional Qualifications:

Knowledge and practical experience of applying supervised machine learning methods, such as regularised regression, ensemble tree-based models (e.g. xgboost) and deep learning methods.
Strong scientific programming skills (ideally in Python) and software engineering skills (OOP, TDD, CI/CD, Docker, MLOps, working with large collaborative code bases) and a track record of working on a range of computational challenges in machine learning development and deployment / productionisation.
A track record of being highly collaborative. This role requires working closely with a diverse cross-functional global team. The ideal candidate enjoys working as part of small project teams, and can break down complex technical requirements into tasks that can be completed across geographies (our team has members in India, Europe and the US).
Excellent verbal and written communication skills, including ability to present technical concepts clearly (in writing, face-to-face discussions and on conference calls), write project analyses, pitch ideas effectively and persuasively to clients / internal stakeholders, provide stakeholders with timely updates on progress, etc.
A proactive, innovative and pragmatic approach to problem solving, including independent research and critical thinking, knowing when to ask for help and gather input, and finding creative solutions to complex methodological and technical problems.
Excellent organisation skills, ability to own complex projects, proactively communicate deadlines and potential delays to stakeholders, and proven ability to deliver results to deadlines.

Bonus Points For:

Interest in growing in the long term into a team management role, responsible for growing a team and formalising team operations.
Experience in an informatics/data science team of a healthcare organisation, including knowledge of healthcare data, EMR integration, types of environments used for data solution development/deployment, etc.
PySpark / big data experience.
Experience in writing your own software packages / tools.
Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilisation, study design etc.

The Team
“Big Data” is changing the way that the healthcare world operates and, now more than ever, the key to better patient outcomes is through better use of technology, seamlessly integrated information and analytics.

Our “AI for Healthcare” team within the Real-World Solutions (RWS) division is a fast-growing group of collaborative, enthusiastic, and entrepreneurial individuals. We are at the centre of IQVIA’s pursuit of machine learning and cutting-edge statistical methods to advance healthcare. Our efforts improve under-diagnosis of rare diseases, personalised treatment response profiles, disease progression predictions, and clinical decision-support tools and have a direct impact on patient care.

You will join this high-profile team to work on ground-breaking problems in health outcomes across disease areas including Ophthalmology, Oncology, Neurology, Chronic diseases (such as diabetes), and a variety of very rare conditions. The team works hand-in-hand with statisticians, epidemiologists and disease area experts across the wider global RWE Solutions team, leveraging a vast variety of anonymous patient-level information. The data encompasses IQVIA’s access to over 530 million anonymised patients as well as bespoke, custom partnerships with healthcare providers and payers.

Learn More
Testimonial video featuring Nadea Leavitt, Senior Director of AI for Healthcare & MedTech at IQVIA, where she talks about why candidates should consider joining our Data Science group at IQVIA:

https://youtu.be/MKXQBncgbs8

What We Offer

Competitive compensation and benefits
A variety of training and development opportunities

We thank all applicants for their interest; however, only those selected for an interview will be contacted.

We invite you to join IQVIA™.

Diversity & Inclusion
IQVIA is a strong advocate of diversity and inclusion in the workplace. We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success. We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximise their personal potential.

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com

IQVIA is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other status protected by applicable law. https://jobs.iqvia.com/eoe

The potential base pay range for this role, when annualized, is $89,400.00 - $223,700.00. The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.","hiringOrganization":{"@type":"Organization","name":"IQVIA","sameAs":"https://www.iqvia.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Wayne, PA, Unites States of America, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":41,"item":{"@type":"JobPosting","title":"Prinicipal, Machine Learning Engineer","datePosted":"2025-09-19","description":"

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

About The Team

The Enterprise Data Science and Innovation team is driving the future of artificial intelligence at Workday. We develop breakthrough solutions using the latest GenAI technology stack while building, maintaining, and monitoring GenAI based solution and ML models that deliver game-changing insights to power critical business functions across Sales, Marketing, Finance, Customer Experience, and other key organizational areas.

Our team consists of diverse and passionate data scientists and ML engineers who are committed to delivering Advanced Analytics insights that directly impact both revenue growth and operational efficiency. We foster a collaborative, supportive work environment where innovation thrives and team members genuinely enjoy working together to solve complex challenges.

About The Role

As a key member of our fast-moving team, you will have the unique opportunity to define and execute the vision for AI and LLM-based systems at scale.You will be at the forefront of developing next-generation AI and Large Language Model based solution that transform how Workday delivers intelligent solutions to our customers and internal stakeholders. We are looking for someone with exceptional programming expertise, deep distributed systems knowledge, and the curiosity and grit to tackle complex, ambiguous challenges. You will work across a diverse technology stack, collaborate closely with engineers and product leaders, and help set the technical direction for AI initiatives while architecting and building robust, scalable AI/LLM platforms from the ground up.

About You

Basic Qualifications

12–15+ years in software, solution, or enterprise architecture with hands-on delivery of production-grade AI/ML systems
Architect, design, and implement production systems in Python (full-stack experience a plus)
Deep expertise in cloud architecture on at least one hyperscaler (AWS, Azure, GCP) with ability to design and optimize cloud-native AI workloads
Proven MLOps and ML platform experience: data pipelines(PySpark), model lifecycle (training, evaluation, deployment), CI/CD, and monitoring
Working knowledge of Generative AI / LLMs: prompting, fine-tuning, and rapid prototyping
Strong foundation in SaaS, multi-tenant architectures, microservices, and APIs—particularly around integrating AI into products and workflows
Excellent communication skills: able to engage both executives (whiteboarding) and engineers (deep technical dives)
Solid understanding of security, privacy, and compliance considerations in enterprise AI (e.g., data governance, model safety)
Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent; advanced degrees or equivalent experience also considered
Mentor and guide engineers from junior to senior levels, fostering technical excellence
Skilled at presenting complex technical topics at both abstract and implementation levels

Preferred Qualfications

Experience with Agentic AI/orchestration frameworks (tool use, lifecycle, interoperability)
Familiarity with LangChain, LLMOps tools, vector search/RAG, retrieval pipelines
Knowledge of Responsible AI practices, including governance, risk, human-in-the-loop, and auditability in enterprise settings
Consulting or industry solutions background, with ability to map domain needs to AI architectures
Recognized technical leadership through publishing, mentoring, or internal standards contributions
Experience aligning AI/ML with enterprise roadmaps and platforms (e.g., Databricks)
Open-source contributions or significant personal technical project

Our Approach to Flexible Work

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote \"home office\" roles also have the opportunity to come together in our offices for important moments that matter.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

","hiringOrganization":{"@type":"Organization","name":"Workday","sameAs":"https://www.workday.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IND.Pune, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":42,"item":{"@type":"JobPosting","title":"Sr. Machine Learning Engineer – Context Engineering","datePosted":"2025-09-19","description":"

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

GEICO is seeking an experienced Sr. Staff Machine Learning Engineer to join our AI org. This person will play key roles for the development of Geico’s virtual assistant platform that elevates the productivity for 30K+ internal associates and the customer experience for millions of policyholders. You will be collaborating with a dynamic team of AI and software engineers to design, develop and deploy systems that ensure scalability, reliability and usability of agentic workflows across Geico. Context engineers build centralized services that ensure seamless ingestion and consumption of internal knowledge and contextual data, giving AI agents comprehensive and up-to-update information to determine optimal next steps. The ideal candidate should demonstrate a proven track record of building high performance AI/ML platform & systems, with hands-on experience and deep enthusiasm for Generative AI and related ecosystems.

Responsibilities:

Own development of key platform components that power end-to-end GenAI agentic workflows. Examples include knowledge curation & management, search, context management, workflow orchestration, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs for high impact business use cases. Establish pragmatic visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Contribute to the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Lead a small team of engineers for feature & system implementation. Troubleshoot and resolve complex software issues, ensuring optimal platform performance and reliability.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Basic Qualifications

5+ years of experience designing and building AIML platform and systems utilizing components such as vectordb (e.g. Qdrant, Milvus, etc.), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgres sql), knowledge graph (e.g. neo4j), workflow orchestration (e.g. Airflow, Temporal).
Proficient in Python, Java and similar general-purpose programming languages.
3+ years’ experience managing end-to-end software development life cycle (e.g. CICD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for backend systems and APIs
2+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

3+ years of experience building enterprise-level semantic knowledge-graph & related capabilities, such as ontology creation, knowledge ingestion, graph queries-based feature engineering, etc.
2+ years’ experience utilizing and/or finetuning open source LLMs, Llama, Mistral, Claude etc. to build conversational experiences and agentic workflows, esp. natural-language-based query engines (e.g. text2sql)
Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments

Annual Salary

$115,000.00 - $230,000.00

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"NY Manhattan (Office) - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":43,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"Machine Learning EngineerData Science Analyst Mid 2

About Flutter Entertainment:

Flutter Entertainment is the world’s largest sports betting and iGaming operator with 13.9 million average monthly players worldwide and an annual revenue of $14Bn in 2024. We have a portfolio of iconic brands, including Paddy Power, Betfair, FanDuel, PokerStars, Junglee Games and Sportsbet.

Flutter Entertainment is listed on both the New York Stock Exchange (NYSE) and the London Stock Exchange (LSE). In 2024, we were recognized in TIME’s 100 Most Influential Companies under the 'Pioneers' category—a testament to our innovation and impact. Our ambition is to transform global gaming and betting to deliver long-term growth and a positive, sustainable future for our sector. Together, we are Changing the Game!

Working at Flutter is a chance to work with a growing portfolio of brands across a range of opportunities. We will support you every step of the way to help you grow. Just like our brands, we ensure our people have everything they need to succeed.

Flutter Entertainment India:

Our Hyderabad office, located in one of India’s premier technology parks is the Global Capability Center for Flutter Entertainment. A center of expertise and innovation, this hub is now home to over 900+ talented colleagues working across Customer Service Operations, Data and Technology, Finance Operations, HR Operations, Procurement Operations, and other key enabling functions.

We are committed to crafting impactful solutions for all our brands and divisions to power Flutter's incredible growth and global impact. With the scale of a leader and the mindset of a challenger, we’re dedicated to creating a brighter future for our customers, colleagues, and communities.

Overview Of The Role:

Our Data Science and AI Competence Center is looking for a motivated and versatile Data Scientist who can design and develop ML/AI solutions while gaining exposure to deploying them in production environments.

As a Data Scientist (MLOps), you will collaborate with an industry-leading team and enhance your skills in delivering groundbreaking solutions to continue driving innovation. This role follows a hybrid approach to working, allowing you to combine working from home with working in our modern office in Hyderabad, India.

What You Will Do:

Build and maintain production-grade ML pipelines and services.
Containerize and deploy ML models using Docker and Kubernetes.
Collaborate with the Data Science team to transition research models from experimentation into production.
Work with large-scale datasets using SQL and Spark.

TO EXCEL IN THIS ROLE, YOU WILL NEED:

A degree qualified in a STEM subject along with 2 to 4 years of experience as a Data Scientist or ML Engineer.
Strong programming skills in Python and proficiency with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
Experience manipulating large datasets using SQL and Spark.
Experience with big data technologies (Spark, Hadoop, Kafka) and cloud platforms (AWS, Google Cloud, Azure)
Solid understanding of machine learning methods (tree-based models, deep learning, etc.)
Hands-on experience in ML model deployment, orchestration and monitoring (Kubernetes, Docker, CI/CD)
Ability to Manage ML-Ops lifecycle (deploy-monitor-maintain-evolve)
Strong communication skills to explain technical concepts to stakeholders.

Benefits We Offer:

Aside from a generous base salary, we have a phenomenal benefits and rewards program that is designed to encourage personal and career development.

This Package Includes:

Access to Learnerbly, Udemy, and a Self-Development Fund for upskilling.
Career growth through Internal Mobility Programs.
Comprehensive Health Insurance for you and dependents.
Well-Being Fund and 24/7 Assistance Program for holistic wellness.
Hybrid Model: 2 office days/week with flexible leave policies, including maternity, paternity, and sabbaticals.
Free Meals, Cab Allowance, and a Home Office Setup Allowance.
Employer PF Contribution, gratuity, Personal Accident & Life Insurance.
Sharesave Plan to purchase discounted company shares.
Volunteering Leave and Team Events to build connections.
Recognition through the Kudos Platform and Referral Rewards.

Why Choose Us:

Flutter is an equal-opportunity employer and values the unique perspectives and experiences that everyone brings. Our message to colleagues and stakeholders is clear: everyone is welcome, and every voice matters. We have ambitious growth plans and goals for the future. Here's an opportunity for you to play a pivotal role in shaping the future of Flutter Entertainment India.

","hiringOrganization":{"@type":"Organization","name":"Flutter International","sameAs":"https://careers.flutterinternational.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hyderabad, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":44,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-19","description":"

Job Posting Title:

Machine Learning Engineer

Req Id:

10131647

Job Description:

About The Role & Team:

“Any sufficiently complex technology is indistinguishable from magic.” - Arthur C. Clarke

At Imagineering, we are constantly exploring new ways to connect with our guests – to surprise them, make them smile, and open their minds to magic - not just in our parks and resorts, but everywhere around the world.

At Walt Disney Imagineering Research and Development, this \"magic\" emerges from the application of world-class technology and everything from new Guest-facing experiences to new tools for Imagineers and Cast Members who power our parks and bring that magic to life. Our team of engineers, designers, artists, and scientists share a passion for solving impossible problems and building ground-breaking experiences.

At Disney Research Imagineering, we pursue and apply the science behind the magic: unlocking new opportunities for Imagineering in all aspects of project lifecycles, from early phase creative ideation to deployment.

We are looking for a Machine Learning Engineer with strong software engineering skills and experience in AI, who thrives in experimental, interdisciplinary environments.

You will work with senior engineers and scientists to prototype, build, and productionize software algorithms, components, and complex systems to support agentic workflows across Disney’s themed entertainment portfolio. Your role will focus on technical execution, software development, and the translation of experimental AI technologies into robust, production-ready tools.

This role will report to the Associate Lab Director and contribute to the AI/ML applied research portfolio at Disney Research Imagineering.

This is a full-time role.

What You Will Do:

Implement and support prototypes of generative AI tools and intelligent agents for creative and technical tasks.
Develop and maintain software pipelines that integrate agentic AI workflows and tooling.
Collaborate with researchers to translate conceptual models and experimental algorithms into working code and functional systems.
Optimize, test, and document systems to support evaluation and deployment within Imagineering teams.
Participate in the integration of AI models with APIs, databases, internal tools, and creative software.
Troubleshoot and iterate on system performance and usability based on feedback from cross-disciplinary collaborators.
Partner with interdisciplinary teams to ensure AI applications empower rather than constrain artistic and storytelling processes.
Collaborate with internal and external research partners, including software teams, business stakeholders, academic institutions, industry labs, and vendors.
Translate scientific insights into working prototypes and production-ready implementations

Required Qualifications & Skills:

3+ years of professional software development experience
Experience using ML/AI and prototyping solutions in academic, entertainment, or industrial settings
Experience with generative models and AI agent architectures.
Strong programming skills in Python and experience with large model libraries, APIs, and support tooling (e.g. OpenAI, Azure, Ollama, MCP, etc).
Excellent collaboration, problem-solving, and communication skills with the ability to present complex ideas to multidisciplinary teams
Demonstrated ability with production-ready, real-world implementations
A desire to work in a collaborative, creative environment where technical and creative experts collaborate and challenge each other every day to achieve truly groundbreaking solutions

Preferred Qualifications:

Proven track record of delivering novel AI solutions in practical contexts
Familiarity with the development, evaluation, and deployment of LLMs, VLMs, and multimodal AI systems
Experience with reinforcement learning, prompt engineering, and fine-tuning generative models
Experience with AI-assisted tools in architecture, entertainment, or XR applications is a plus.
Track record of technology transfer, patents, or deployed AI systems
Contributions to open-source projects or prior work in research labs or innovation teams
Interest in construction tech, architecture, or fabrication workflows is a plus.

Education:

Bachelor's in Computer Science, Electrical Engineering, Computational Design, or a related field. Specialization in AI/ML preferred.

Additional Information:

Benefits and Perks: Disney offers a rewards package to help you live your best life. This includes health and savings benefits, educational opportunities, and special extras that only Disney can provide. Learn more about our benefits and perks at https://jobs.disneycareers.com/benefits.

#Dxmedia

#Li-Kk2

The hiring range for this position in Glendale, CA, is $114,900-$154,100 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Job Posting Segment:

WDI R&D and Tech Studio

Job Posting Primary Business:

R&D and Tech Studio (WDI)

Primary Job Posting Category:

Machine Learning

Employment Type:

Full time

Primary City, State, Region, Postal Code:

Glendale, CA, USA

Alternate City, State, Region, Postal Code:

Date Posted:

2025-09-19","hiringOrganization":{"@type":"Organization","name":"The Walt Disney Company","sameAs":"https://thewaltdisneycompany.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"USA - CA - 521 Circle Seven Dr, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":45,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer – AI Agent Platform","datePosted":"2025-09-19","description":"

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

Responsibilities:

Own design, development and maintenance of high-performance, durable and scalable platform components that jointly power large sets of end-to-end GenAI agentic workflows. Examples include AI agent building & deployment, prompt management, workflow orchestration, MCP registry, etc.
Contribute to the selection, evaluation, and implementation of software platforms, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Basic Qualifications

5+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python or C#.
4+ years of experience designing and building AIML platform and systems utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. MongoDB, Cassandra), distributed processing (e.g. Spark, Ray), workflow management (e.g. Airflow, Temporal), memory management (e.g. Redis), etc.
3+ years’ experience managing end-to-end software development life cycle (version control, CICD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support etc.)
3+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

3+ years’ experience with cloud providers such as Azure and AWS
2+ years’ experience building conversational experiences and agentic workflows, leveraging open source LLMs, e.g. Llama, Mistral, Claude etc.
Experience with LLM observability software such as Langsmith, Arize Phoenix, etc.
Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments

Annual Salary

$115,000.00 - $230,000.00

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"MD Chevy Chase (Office) - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":46,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

About Us

Staff Engineer – Machine Learning (E4)

Job Description

Key Responsibilities

Build intelligent agentic systems that combine document understanding, retrieval, and LLM-based reasoning to support context-aware conversational workflows.
Design and implement scalable Agentic RAG pipelines that orchestrate unstructured data preprocessing, vector store integration, and LLM prompting for accurate, grounded responses.
Develop modular ML components for layout analysis, information extraction, dialogue management, and tool invocation within multi-turn, goal-driven conversations.
Integrate conversational agents with enterprise data sources, APIs, and downstream automation workflows to enable end-to-end task execution.
Craft dynamic prompting and memory strategies to maintain context, reduce hallucination, and improve relevance in long-form or multi-turn queries.
Collaborate cross-functionally with product managers, UX designers, and platform engineers to define agent behavior and ensure seamless user experiences.
Monitor and continuously improve system performance, including response quality, retrieval precision, latency, and task success rate using real-world feedback.
Drive data curation efforts including synthetic generation, annotation workflows, and hard example mining to improve agent robustness and generalization.
Establish best practices for evaluating agent behavior, including human-in-the-loop review processes, regression testing, and safety guardrails.
Contribute to infrastructure and MLOps pipelines that support model experimentation, deployment, and monitoring in production environments.

Qualifications / Expectations:

Bachelor’s or Master’s Degree in Computer Science, Data Science, or a related technical field. Advanced degrees are a plus.
5–7+ years of hands-on experience in building and deploying machine learning models, with a strong focus on document intelligence, NLP, or Generative AI.
Proven experience developing and productionizing ML systems for unstructured data processing, including document parsing, table extraction, and layout analysis.
Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and experience with OCR and document processing tools (e.g., Tesseract, AWS Textract, PDFMiner, LayoutParser).
Strong experience with LLMs and Retrieval-Augmented Generation (RAG) architectures, including practical knowledge of LangChain, LlamaIndex, Haystack, or similar frameworks.
Experience building ML pipelines and implementing MLOps best practices to support training, validation, deployment, and monitoring of models at scale.
Hands-on experience with cloud ML services (e.g., AWS SageMaker, Azure ML, Google Vertex AI) for training and inference.
Solid programming skills in Python, with working knowledge of SQL
Experience with containerization (Docker), orchestration (Kubernetes), and model serving technologies (e.g., Triton Inference Server, ONNX Runtime, TorchServe) in production environments.
Knowledge of model optimization techniques (e.g., quantization, pruning, distillation) to improve inference efficiency on cloud or edge devices.
Strong problem-solving abilities, with a track record of delivering scalable, high-impact ML solutions for complex, real-world problems.
Excellent communication skills and ability to work autonomously in a fast-paced, collaborative environment.
Understanding on knowledge graphs and graph based information retrieval
Experience designing and integrating conversational agents with context memory, function/tool calling, and dynamic prompting strategies.
Familiarity with vector stores (e.g., FAISS, Pinecone, Weaviate) and search/retrieval mechanisms for grounding LLM outputs.

Nice To Have:

Experience in fine-tuning large language models (LLMs) and applying GenAI techniques in parsing unstructured data.
Experience with dialogue management systems or conversational frameworks (e.g., Rasa, Dialogflow, or custom pipelines) for building intelligent agents.
Experience with distributed training techniques to optimize large-scale model training across multiple GPUs or cloud environments.
Understanding of prompt engineering best practices and few-shot or chain-of-thought prompting for improving agent behavior in GenAI systems.
Background in open-source contributions or research related to document AI, LLM applications, or multi-modal learning.
Familiarity with CI/CD pipelines for ML, automated model versioning, and monitoring tools for performance and drift in production models.

All unsolicited resumes submitted to any @automationanywhere.com email address, whether submitted by an individual or by an agency, will not be eligible for an agency fee.

","hiringOrganization":{"@type":"Organization","name":"Automation Anywhere","sameAs":"https://www.automationanywhere.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IN Bengaluru, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":47,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, Data Infrastructure","datePosted":"2025-09-18","description":"

Persona AI is developing and commercializing rugged, multi-purpose humanoid robots that perform real work. Persona’s founding team has a decades-long history in humanoid robotics, bionics, and product development delivering robust hardware that has touched the stars, worked miles below the surface of the ocean, and even roamed Disney Parks. Our mission is focused squarely on shipping beautiful, reliable products at massive scale, while building a customer-focused team to achieve these aims.

We're looking for an exceptional Machine Learning Engineer (Data Infrastructure) who dreams big, thrives on challenges, and loves building the infrastructure that powers intelligent robots at scale. You have a passion for data systems and believe magic happens when massive datasets become actionable insights.

We are primarily interested in candidates who have built production-grade data infrastructure that enables machine learning at scale. As a Machine Learning Engineer (Data Infrastructure) at Persona, you will have an incredible opportunity to design the data backbone that enables our humanoid robots to learn and improve continuously from real-world interactions. If you're passionate about creating technology that seamlessly scales from individual robots to global fleets and want to be part of a world-class team, we'd love to hear from you.

Your Role:

Responsible for designing and implementing data pipelines for the entire data lifecycle from robot hardware, on-prem servers, to cloud storage.
Manage data versioning and monitor robot data quality with qualitative metrics important to Persona AI’s Machine Learning objectives.
Write robust and performant software to curate, transfer, and store large quantities of data from our robot fleets.
Collaborate closely with ML and robotics engineers to continuously maintain and improve the data pipelines.
Design on-robot triggers that determine if and when robot data should be uploaded.
Automate ETL pipelines to make fleet-wide data easily queryable and available to train on.
Automate data movement between data farms and deployment to cloud datacenters
Build frontend tools for visualizing and automating labeling of web-scale datasets.

We'Re Looking For:

A production-oriented engineering mindset with experience shipping reliable, scalable systems.
A performance optimization savvy who is not only comfortable with low-level bits and multithreading, but also with high-level distributed systems.
Expertise in Python and experience with C++ and distributed computing frameworks.
A friendly, collaborative mindset, strong communication skills, and excitement to work hands-on in a dynamic, supportive team environment.
A comprehensive portfolio demonstrating your specific contributions to large-scale data infrastructure projects.

Preferred Or Bonus Qualifications:

Have built a petabyte-scale data-engine to handle a fleet of robots.
Experience with the following technologies: Databases, Ansible, Docker.
Familiar with general robotics and robot learning algorithms.
Experience with edge computing and data synchronization in robotics applications.

Why join Persona AI?

You'll shape technology that's redefining the possibilities of robotics and human interaction.
Work alongside passionate teammates who value diversity, creativity, and continuous learning.
Enjoy full access to advanced prototyping tools, labs, and the freedom to experiment and innovate.
We offer competitive compensation, excellent benefits, flexible work environment, and equity opportunities.

Not sure if you meet all the listed qualifications? That’s okay!
We encourage you to apply anyway. Our needs are constantly evolving, and we're always looking for talented individuals who can grow with us. You might be exactly who we’re looking for — even if it’s for a role we haven’t thought of yet.

Persona Ai Embraces Diversity And Equal Opportunity In A Serious Way. We Are Committed To Building A Team That Represents A Variety Of Backgrounds, Perspectives, And Skills. We Believe The More Inclusive We Are, The Better Our Work Will Be.

","hiringOrganization":{"@type":"Organization","name":"Persona AI","sameAs":"https://personainc.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pensacola, FL or Houston, TX","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":48,"item":{"@type":"JobPosting","title":"Senior Applied Machine Learning Engineer, Frontier AI","datePosted":"2025-09-18","description":"

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

About The Team

Anduril’s Lattice software platform integrates together many sensors into a single cohesive view of the world, providing needed context for our users. AI Engineers on Anduril’s Frontier AI team build edge-compatible, generative AI systems into the Lattice software platform to provide features and products that improve autonomy and reduce cognitive burden on the warfighter. Specific applications include but are not limited to automating mission planning, battle-space understanding, voice-control of assets, and enabling higher-levels of autonomy.

What You'Ll Do

Distill and fine-tune transformer architectures so they can be deployed onto edge devices or compute denied environments
Propose and prototype LLM-based Agentic systems that help solve real world problems, leveraging the latest state-of-the-art techniques in the field
Develop and maintain mission relevant benchmarks
Work cross-functionally with different business lines across Anduril to help discover and scope new research problems.

Required Qualifications

BS in Computer Science, Machine Learning, Electrical Engineering, or related field
5+ years experience developing and benchmarking ML algorithms
Experience pushing and maintaining ML algorithms in production
Strong Python skills with experience in ML frameworks such as PyTorch
Must be a U.S. Citizen and eligible to obtain and maintain a U.S. Government clearance

Preferred Qualifications

Experience fine-tuning transformer-based model
Experience deploying deep-learning based models to edge devices or air gapped environments
Prior experience in defense tech or start-up

US Salary Range$168,000—$252,000 USDUS Hourly Range $168,000—$252,000 USD\n

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:

Platinum Healthcare Benefits: For U.S. roles, we offer comprehensive medical, dental, and vision plans at little to no cost to you.\n\n
Basic Life/AD&D and long-term disability insurance 100% covered by Anduril, plus the option to purchase additional life insurance for you and your dependents.
Extremely generous company holiday calendar including a holiday hiatus in December, and highly competitive PTO plans.
16 weeks of paid Caregiver & Wellness Leave to care for a family member, bond with your baby, or tend to your own medical condition.
Family Planning & Parenting Support: Fertility (eg, IVF, preservation), adoption, and gestational carrier coverage with additional benefits and resources to provide support from planning to parenting.
Mental Health Resources: We provide free mental health resources 24/7 including therapy, life coaching, and more. Additional work-life services, such as free legal and financial support, available to you as well.
A professional development stipend is available to all Andurilians.
Daily Meals and Provisions: For many of our offices this means breakfast, lunch and fully stocked micro-kitchens.
Company-funded commuter benefits available based on your region.
Relocation assistance (depending on role eligibility).
401(k) retirement savings plan - both a traditional and Roth 401(k). (US roles only)
For UK roles, Private Medical Insurance (PMI): Anduril will cover the full cost of the insurance premium for an employee and dependents.
For AUS roles, Private health plan through Bupa: Coverage is fully subsidized by Anduril.

The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Anduril is an equal-opportunity employer committed to creating a diverse and inclusive workplace. The Anduril team is made up of incredibly talented and unique individuals, who together are disrupting industry norms by creating new paths towards the future of defense technology. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws, including the CA Fair Chance Initiative for Hiring Ordinance. We actively encourage members of recognized minorities, women, Veterans, and those with disabilities to apply, and we work to create a welcoming and supportive environment for all applicants throughout the interview process. If you are someone passionate about working on problems that have a real-world impact, we'd love to hear from you!

To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.

","hiringOrganization":{"@type":"Organization","name":"Anduril","sameAs":"https://www.anduril.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, Massachusetts, United States; Costa Mesa, California, United States; Washington, District of Columbia, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":49,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Domains Search","datePosted":"2025-09-18","description":"

The Domains Search team at Squarespace is building the next generation of intelligent search experiences for helping customers find the perfect domain. From applying large language models to produce creative domain suggestions, to building scalable ranking and personalization systems, our team is at the intersection of applied machine learning, natural language processing, and large-scale search infrastructure.

We are looking for a Senior Machine Learning Engineer to help shape and build this platform from the ground up. You will report to an Engineering Team Lead in our New York City headquarters.

Why Join Us

This is a unique opportunity to shape a greenfield ML initiative at Squarespace. You'll be part of a small, high-impact team building the foundation of how millions of customers discover and secure their online identity.

You'Ll Get To...

Design, build, and deploy ML models for domain search, including ranking, personalization, and generative domain name creation. Integrate and fine-tune LLMs and hybrid systems (LLMs + rule-based + classical ML) to create brandable, contextual, and internationalized domain suggestions.
Develop and evaluate ranking algorithms that optimize for multiple signals such as relevance, uniqueness, brandability, and business goals.
Implement personalization approaches leveraging user, account, and demographic data to tailor search results.
Collaborate with engineers, data scientists, and product managers to translate ambiguous product ideas into technical requirements and scalable ML solutions.
Own end-to-end ML lifecycle: from feature engineering, model training, and evaluation to deployment, monitoring, and iterative improvement.
Contribute to experimentation frameworks (A/B testing, Statsig, etc.) to measure model impact and continuously improve user experience.
Ensure search quality at scale by developing robust evaluation pipelines and metrics.

Who We'Re Looking For

5+ years of professional experience in machine learning engineering, with at least 2 years at a senior/lead IC level.
Strong background in search, ranking systems, or recommendation engines.
Experience with NLP and LLMs (prompt engineering, fine-tuning, or integration into production systems).
Proficiency in Python, ML frameworks (TensorFlow, PyTorch), and data tooling (Spark, SQL).
Experience deploying ML models to production and scaling them to handle large traffic volumes.
Familiarity with A/B testing and online experimentation methodologies.

Benefits & Perks

A choice between medical plans with an option for 100% covered premiums
Fertility and adoption benefits
Access to supplemental insurance plans for additional coverage
Headspace mindfulness app subscription
Global Employee Assistance Program
Retirement benefits with employer match
Flexible paid time off
20 weeks for parental leave and up to 12 weeks to care for an ill family member
Pretax commuter benefit
Education reimbursement
Employee donation match to community organizations
8 Global Employee Resource Groups (ERGs)
Dog-friendly workplace
Free lunch and snacks
Private rooftop
Hack week twice per year

Cash Compensation Range: $128,500 - $231,500 Usd

The base salary for this position will vary based on job-related criteria including relevant skills, experience, and location, among other factors.

In addition to the cash compensation above (which includes base salary and, where applicable for eligible roles, may include on-target commissions or overtime pay), Squarespace employees are eligible to be granted an option to purchase our common stock.

About Squarespace

Squarespace is a design-driven platform helping entrepreneurs build brands and businesses online. We empower millions of customers in more than 200 countries and territories with all the tools they need to create an online presence, build an audience, monetize, and scale their business. Our suite of products range from websites, domains, ecommerce, and marketing tools, as well as tools for scheduling with Acuity and creating and managing social media presence with Bio Sites and Unfold. Our team of more than 1,500 is headquartered in bustling New York City, with offices in Dublin, Ireland, Aveiro, Portugal, and coworking spaces in the UK, Netherlands, and Australia. For more information about our company culture, visit https://www.squarespace.com/about/careers.

Our Commitment

Today, more than a million people around the globe use Squarespace to share different perspectives and experiences with the world. Not only do we embrace and celebrate the diversity of our customers, but we also work toward the same in our employees. At Squarespace, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We are proud to be an equal opportunity workplace.

#Li-Hybrid

Thank you in advance for providing the following details about your work history from your resume! This helps us ensure that your candidate information is accurate and consistent during the hiring process.

\n\n

Squarespace will never solicit your personal banking information or ask you to transfer money in connection with a job offer or interview. We also will not reach out to you via phone or SMS without your permission or knowledge.

","hiringOrganization":{"@type":"Organization","name":"Squarespace","sameAs":"https://www.squarespace.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":50,"item":{"@type":"JobPosting","title":"Machine learning Engineer","datePosted":"2025-09-18","description":"

Company Description

Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.

Job Description

What you will do
\nAs an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global.

Your Responsibilities Include:

Leading an internal team towards the development of AI products;
Working in a multidisciplinary team on client projects as an expert on your subject;
Making architectural and design decisions for cloud environments;
Building production level ML/AI solutions with solid software engineering;
Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping);
Giving trainings, leading internal meetings and organizing external events;
Participating in team meetings and workshops with clients;
Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead.

Who you will work with
\nThe Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together.

Who You Are

You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities.
You have first-rate project management and time management skills.
You are a true problem solver, you turn complex issues into simple and impactful business solutions.
You are enthusiastic for applying Data Science/Engineering solutions to business problems.
You have excellent communication skills and can present complicated concepts in a synthetic way.
You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment.
You have the ability to work collaboratively in a team environment.

In Return, You Can Expect:

An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions.
A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged
A personal development plan with a regular follow-up as well training opportunities to develop yourself
A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,...

Qualifications

MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study.
2-4 years of experience in building production-quality ML/Deep Learning pipelines and models.
Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP).
Expert coding skills in Python and at least one of these languages: Scala, C++, Java.
Hands-on experience with database management languages (e.g., SQL, PostgreSQL).
Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure).
Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes).
Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks).
Experience with coaching/mentoring other engineers.
Prior experience in Management Consulting is a strong plus.
Willingness to travel and work at local and international clients.
Fluency in spoken and written English is required.
Ability or strong willingness to be professionally proficient in the Dutch language.

Additional Information

We are unable to provide a work permit for this position

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. 

","hiringOrganization":{"@type":"Organization","name":"Sia","sameAs":"https://www.sia-partners.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Amsterdam, NH, Netherlands","addressCountry":"The Netherlands","addressRegion":"Europe"}}}}]}

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