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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

Ready to make a global impact by industrializing AI?

About The Role:

Visa AI as a Service (VAIaS) operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, VAIaS automates the updates to data, models, and applications. Combined with strong AI governance, VAIaS optimizes the performance, scalability, interpretability and reliability of AI models and services. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you!

We are looking for a talented and versatile entry-level Machine Learning Engineer to join our growing team. In this role, you will be a key contributor to the full lifecycle of our core machine learning infrastructure. You will be responsible for both building our high-performance, low-latency model inference engine and ensuring its rock-solid reliability through a best-in-class observability platform.

This is a role for a strong software and machine learning engineering generalist who is passionate about building robust, scalable systems. You will be empowered to solve complex problems, write production-grade code, and make a significant impact on the systems that power our intelligent products.

Key Responsibilities:

Design, build, and maintain the full lifecycle of our machine learning systems, from our low-latency inference engine to the observability platform that supports it.
Develop and optimize high-performance, mission-critical services using languages like Rust, Python, and Go.
Enhance the reliability and visibility of our MLOps ecosystem by building and scaling solutions for monitoring, logging, and tracing.
Collaborate closely with data scientists and ML engineers to deploy, scale, and troubleshoot machine learning models in production.
Write clean, high-quality, and well-tested code, and participate in code reviews to raise the bar for the entire team.
Diagnose and resolve performance bottlenecks and system failures in our production environment.

If you are passionate about machine learning, model inference technology, large scale low latency system and are excited about making a significant impact, we would love to hear from you.

This is a hybrid position based in Austin, TX, allowing alternating between remote and office work. Expectations are to be in-office at least three days a week, aiming for a 50% office presence based on business requirements.

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).

Preferred Qualifications

Strong programming proficiency in at least one of the following languages: Rust/C++/Go/Java
A strong desire to learn and a passion for building impactful, high-performance systems.
Experience with performance optimization.
Hands-on experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
Familiarity with observability tools (e.g., Prometheus, Grafana, OpenTelemetry) and cloud platforms (AWS, GCP, Azure).
Knowledge of network programming, gRPC, Protocol Buffers, or other RPC frameworks.
Experience working on large-scale distributed systems.

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 $116,500.00 to $164,500.00 USD 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":2,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-23","description":"

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

What you get to do in this role:

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

Build the best cloud-based AI/ML solutions to power intelligent enterprise services
Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software
Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users

Qualifications

To be successful in this role you have:

A Bachelor's degree and 2+ years of related experience; or an advanced degree without experience; or equivalent work experience
Proficient in prompt engineering and developing LLM based features
Experience with methods of training and fine tuning large language models, such as distilation, supervised fine-tunning and policy optimization
Experience in using Al productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
Expertise in Java or Python, OOP, Design Patterns, time and space-efficient algorithms
Experience building new products that use challenging algorithms
Expertise in coding efficient, object-oriented, modularized and quality software
Knowledge of core AI/ML techniques and algorithms
Knowledge of unit testing, profiling, and code tuning

For positions in this location, we offer a base pay of $137,300 - $212,900, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

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":"Santa Clara, California , United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":3,"item":{"@type":"JobPosting","title":"Machine Learning Engineer (Python)- IFS TheLoops","datePosted":"2025-09-23","description":"

Company Description

IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.

At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust.

We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.

By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.

We’re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.

If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS.

Job Description

We are looking for a motivated Machine Learning Engineer (Python) to join our fast-moving team. This is a hands-on role ideal for someone with a solid foundation in machine learning, strong Python skills, and a desire to grow in a dynamic and often ambiguous environment. You’ll work closely with product managers, data scientists, and engineers to rapidly prototype, test, and deploy ML-driven features and pipelines.

What You’Ll Do

Collaborate in an agile team to develop and deploy ML models and data pipelines.
Translate loosely defined business or customer requirements into practical ML solutions.
Be creative and proactive in shaping solutions that solve real-world problems.
Build, test, and optimize scalable Python-based systems for training and inference.
Work with structured and unstructured data (e.g., tabular, text, image).
Participate in sprint planning, daily stand-ups, and reviews.
Own and maintain parts of the codebase and contribute to improving engineering best practices.

Qualifications

What We’re Looking For

2–4 years of experience in software engineering or ML engineering roles.
Strong Python programming skills with experience in ML frameworks like scikit-learn, TensorFlow, or PyTorch.
Proficiency with data handling libraries (e.g., pandas, NumPy) and tools like Jupyter.
Ability to take customer or business requirements and creatively turn them into technical solutions.
Exposure to common ML workflows: data cleaning, feature engineering, model evaluation.
Comfortable working in a fast-paced, agile environment with changing priorities and some ambiguity.
Good communication and collaboration skills; you’re proactive and not afraid to ask questions.
Familiarity with version control (e.g., Git) and containerization (e.g., Docker).
Experience with cloud platforms (AWS, GCP, or Azure) and basic understanding of MLOps practices.
Exposure to CI/CD workflows and tools like MLflow or model serving frameworks.
Ability to build lightweight APIs (e.g., FastAPI, Flask) to expose models is a plus.

Additional Information

We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.

","hiringOrganization":{"@type":"Organization","name":"IFS","sameAs":"https://www.ifs.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Colombo, WP, Sri Lanka","addressCountry":"Sri Lanka","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":4,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - Intern","datePosted":"2025-09-23","description":"We Make a Future Classic Product!
채널톡은 기업의 지속가능한 성장을 돕는 ‘올인원 AI 메신저’입니다. 고객과 언제 어디서나 대화할 수 있는 환경을 만들어 비즈니스의 방향성을 고객으로부터 찾을 수 있도록 돕고 있어요.
현재 '고객이 답이다'라는 철학으로 고객사의 고객 소통 경험을 변화시키고 있습니다. CRM 데이터 기반의 상담 경험 설계와 AI를 통한 반복 문의를 빠르게 처리해 CS 효율화부터 고객 경험 개선까지 채널톡 하나로 해결해요.
수많은 온라인 비즈니스의 본질적인 문제를 풀어낸 결과 한국 너머의 시장에서도 빠르게 성장하고 있습니다. 일본 시장에서 점유율 20% 이상으로 업계 1위와 매출 성장세도 B2B 업체 중 아시아에서 가장 빠른 수준이에요. 아시아에서 인정받은 제품력을 발판 삼아 글로벌 SaaS 기업으로 거듭나고자 미국 시장에 적극 진출하고 있습니다.
채널톡 출시 이후 이와 같은 성과를 거둘 수 있었던 핵심은 ‘제품’입니다. 좋은 제품이 최고의 세일즈, 마케팅이라고 믿습니다. 채널팀 전체 임직원 중 절반 이상이 개발자로 이들 모두가 단 하나의 제품을 만드는데 집중합니다. 구글 검색, 아이폰처럼 한 세대를 상징할 “미래의 클래식” 프로덕트를 목표로 최고의 인재들과 함께합니다.
하고 싶은 일이 참 많습니다! 많이 기대되는 앞으로의 여정 가운데 함께할 채널톡의 Machine Learning Engineer - Intern을 찾습니다!
[채널팀이 더욱 궁금하다면?🧐]🏡 홈페이지💡블로그🖥 유튜브💌 인스타그램\n

어떤 기회가 있나요?🚀

상담 문제를 넘어, 비즈니스 전반에서 AI 기술로 고객의 문제를 해결하는 과정을 end-to-end로 경험할 수 있습니다.
채팅 및 음성 기반의 상담봇 시스템에 필요한 기반 기술 연구를 직접 주도적으로 하실 수 있습니다.
데이터셋 및 학습된 모델 공개 등으로 오픈 소스 커뮤니티에 기여할 수 있습니다.
최신 LLM 기반 음성 모델 연구에 참여할 수 있습니다.

어떤 업무를 담당하나요?🤔

상담 에이전트 서비스 (ALF) 개선
텍스트, 오디오 등 도메인의 특성에 맞게 최적화된 에이전트 구현
단순 질의응답이 아닌 다양한 태스크를 수행할 수 있는 에이전트 워크플로우 개선
Context engineering을 통한 에이전트 성능 개선
상담 에이전트 평가용 내부 벤치마크 구축 및 개선

데이터 전처리 파이프라인 구축 및 학습
다양한 소스로부터 주어진 문제에 적합한 데이터 수집 및 퀄리티 관리
모델 및 파이프라인 최적화로 효율적인 전처리 파이프라인 구축 (Ray 기반 분산처리, inference acceleration)
다양한 데이터 레시피로 LLM 및 Flow Matching 기반 모델 학습 실험 수행

어떤 경력과 역량이 필요한가요?📖

컴퓨터 과학, 전자공학, 수학, 통계학 등 해당 포지션과 관련된 전공의 학사 이상의 학위를 가지고 계신 분
LLM 모델에 대한 구체적인 이해 및 실제 학습 경험
목표에 맞는 데이터 구축 및 학습 레시피 구축 경험
모호한 상황에서의 문제 정의, 액션 아이템 도출, 실행 및 평가 등 문제 해결 파이프라인을 반복적으로 빠르게 수행하실 수 있는 분
Python 및 LLM 개발 관련 Library나 Platform(PyTorch, Hugging Face) 활용 능력을 갖추신 분

이런 점이 있으면 더 좋아요😊

관련 전공 석사 이상의 학위를 가지고 계신 분
대량의 데이터셋을 수집하고 정제한 경험이 있으신 분
AI 주제의 논문을 작성해보시거나 오픈소스 및 경진대회 활동 경력이 있으신 분
LLM 기반 AI 에이전트를 Production 레벨에서 구현/배포/운영해본 경험이 있으신 분

어떤 방식으로 채용하나요?🏃

일반적으로 서류 제출 - 1차 인터뷰 - 2차 인터뷰 순서로 진행됩니다.
제출하신 서류를 통해 팀에 필요한 기본적인 문제해결 역량을 가지신 분인지 확인합니다. 지금까지 진행하셨던 프로젝트들과 도전 과제들을 어떻게 해결하셨는지 적어주시면 많은 도움이 됩니다.
1차 인터뷰는 1시간 소요되며, 수행하셨던 프로젝트에 대한 내용을 발표하고 관련 질의응답을 진행하게 됩니다. 지원자의 창의적인 문제 해결 능력을 확인하는 데에 중점을 둡니다. 결과 뿐만 아니라 문제를 해결해가는 과정 자체도 중요하게 평가합니다.
2차 인터뷰는 1시간 소요됩니다. 채널과 핏이 잘 맞는 분인지 알기 위해 편안하게 서로 질문을 할 수 있는 시간을 갖게 됩니다.
채용 프로세스는 과제나 면접 결과에 따라 면접 절차를 유동적으로 조정될 수 있습니다.

[아래의 개인정보 처리방침에 동의하고 입사지원하시는 경우 지원자의 개인정보는 다음과 같이 국외이전 됨을 확인하고 동의 합니다.]- 이전받는 자 및 이전 되는 국가 : Lever / 미국- 이전되는 개인정보 항목 : 이름, 이메일, 연락처 및 관련서류- 이전목적 및 보유기간 : 채용절차 진행 / 2년**개인정보 국외이전에 동의하지 않을 수 있으나 최종 입사지원서 제출이 불가하며, 지원하기를 누르시면 동의함으로 간주합니다.","hiringOrganization":{"@type":"Organization","name":"Channel Talk","sameAs":"https://channel.io/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"서울 강남구 논현로 508, GS강남타워","addressCountry":"South Korea","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":5,"item":{"@type":"JobPosting","title":"Machine Learning Engineer / Researcher (Computer Vision – Optimization & Quantization)","datePosted":"2025-09-23","description":"

We are looking for individuals who are passionate about pushing the boundaries of computer vision while also delivering efficient, production-ready models. Candidates with a strong record of open-source contributions or a demonstrable portfolio of impactful ML projects will stand out.

Key Responsibilities

Design, implement, and optimize image/video ML models for large-scale generative AI applications.
Apply advanced techniques such as quantization, pruning, fine-tuning, and model distillation to improve efficiency and performance.
Work with deployment frameworks (ONNX, TensorRT, CUDA) to enable scalable inference.
Collaborate with researchers to bridge state-of-the-art techniques with production-grade engineering.
Conduct experiments, benchmark models, and document findings.
Share insights and collaborate with the broader ML research/engineering team.
Bachelor’s, Master’s, or PhD in Computer Science, AI, Machine Learning, or related fields.
Hands-on experience with deep learning frameworks: PyTorch (preferred), TensorFlow, or JAX.
Strong background in optimization techniques (quantization, pruning, distillation, mixed precision).
Experience with deployment toolkits: ONNX, TensorRT, CUDA, or similar.

Required Qualifications

Demonstrated work in image/video model training, fine-tuning, or adaptation.
Proficiency in Python and familiarity with large-scale GPU-based training.
Experience with GGUF, ComfyUI, or other model deployment ecosystems.
Contributions to open-source computer vision or ML frameworks.
Research or industry experience with foundational/generative models (diffusion, transformers, multimodal).
Familiarity with scaling ML models in distributed systems.
Please share your GitHub profile showcasing open-source work in ML/Computer Vision.

Preferred Qualifications

Portfolio / Contribution Requirement

If unavailable, provide a portfolio of projects, research papers, or documented achievements in model development, training, or optimization.

","hiringOrganization":{"@type":"Organization","name":"Vyro","sameAs":"https://vyro.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"China, China","addressCountry":"China","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":6,"item":{"@type":"JobPosting","title":"Lead Machine Learning Engineer","datePosted":"2025-09-23","description":"

About The Role:

Grade Level (For Internal Use):

About The Role:

We are seeking a Lead Machine Learning and MLOps Engineer focused on Generative AI to join our ML team within the Data Science Center of Excellence at S&P Global. In this role, you will lead engineering activities to build production-grade generative AI solutions and play a pivotal role in implementing machine learning engineering operations to ensure seamless deployment, monitoring, and management of our machine learning models and data pipelines.

The Team:

You will work closely with a world-class AI and ML team comprised of experts in AI and ML modeling, MLOps engineers, data science, and data engineering. Your contributions will be critical in engineering and developing solutions for ML operations, supporting S&P’s AI-driven transformation to drive value both internally and for our customers. This role presents a unique opportunity for ML/MLOps engineers to advance in their career journey.

Responsibilities And Impact:

Lead ML Engineering to architect, build, and deploy production-grade generative AI services and solutions.
Work on large-scale distributed systems, including infrastructure, data ingestion platforms, relational and non-relational databases, microservices, orchestration services, and more.
Oversee MLOps platform development and automated pipelines focused on deploying, monitoring, and maintaining models in production environments, ensuring model governance and optimizing cost and performance.
Collaborate with cross-functional teams to integrate machine learning models into production systems.
Create and manage documentation and knowledge base, including development best practices and MLOps processes and procedures.
Work closely with technology teams in the development and implementation of an enterprise AI platform..

What We’Re Looking For:

Basic Required Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field.
5 years of progressive experience in machine learning, data analytics, or similar roles.
5 years of relevant experience in:
Writing production-level, scalable code.
MLOps, machine learning engineering, big data, or a related role.
Working with relational and non-relational databases, data processing frameworks, and data orchestration.
Containerization, cloud platforms, CI/CD, and workflow orchestration.
Distributed systems programming and AI/ML solutions architecture.

Additional Preferred Qualifications:

2-3 years of experience operationalizing data-driven pipelines for large-scale batch and stream processing analytics solutions.
Experience contributing to research projects or participating in data science competitions.
6-12 months of experience working with generative AI use cases and relevant engineering practices.

About S&P Global Ratings
At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions.

S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.

For more information, visit www.spglobal.com/ratings

What’s In It For You?

Our Purpose:

Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world.

Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress.

Our People:

We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference.

Our Values:

Integrity, Discovery, Partnership

At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.

Benefits:

We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
Our benefits include:
Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global:

At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

S&P Global has a Securities Disclosure and Trading Policy (“the Policy”) that seeks to mitigate conflicts of interest by monitoring and placing restrictions on personal securities holding and trading. The Policy is designed to promote compliance with global regulations. In some Divisions, pursuant to the Policy’s requirements, candidates at S&P Global may be asked to disclose securities holdings. Some roles may include a trading prohibition and remediation of positions when there is an effective or potential conflict of interest. Employment at S&P Global is contingent upon compliance with the Policy.

Recruitment Fraud Alert:

If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.

-----------------------------------------------------------

Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. 

US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf

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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:

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":"SGP - Central Singapore - Corp - Temasek Blvd","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":8,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer – AI Research","datePosted":"2025-09-23","description":"

Job Description

Our AI Research team, reporting directly to the Chief AI Officer, is pioneering how cutting-edge machine learning can transform the way vehicles are designed, manufactured, and experienced. We are building the next generation of intelligent systems—integrating multimodal foundation models, generative AI, and robotics into real-world automotive innovation at global scale.

As a Staff Machine Learning Engineer on the AI Research team, you will serve as a founding member guiding GM’s most ambitious AI initiatives. You will participate in the design, prototyping, and deployment of state-of-the-art AI models with direct application to vehicle design, manufacturing operations, robotics, and simulation of physical systems. Beyond technical execution, you will shape and implement GM’s AI research agenda, join a world-class team of scientists and engineers, and represent GM in the global AI community.

What You’Ll Do

You will participate in a unique work environment which combines leading edge AI/ML research with immediate applications to exciting opportunities to make safer, more efficient cars. We have close working connections to world class engineers in the automotive design space to jointly develop novel applications of AI tools in this space.
Evaluate, prototype and implement impactful AI solutions to design and manufacturing operations at GM. Potential applications include the use of foundation models to large scale design tasks, using generative AI technologies for defining robotics tasks and the application of generative AI to interface with, and develop new technologies for the design and modeling physical systems.
Develop plans and execute projects to integrate AI into GM’s manufacturing, vehicle design, software development, customer support and other products and processes
Be on the forefront of AI models and architecture, making informed decisions on technology adoption and investment
Participating in the research, design, and prototyping of advanced AI models (foundation models, generative AI, multimodal architectures) applied to automotive and robotics domains.
Translate breakthrough AI research into scalable, production-ready systems across design, manufacturing, software, and customer experience.
Join a high-performing team of machine learning researchers and engineers.
Collaborate with product, design, and engineering leaders to identify high-impact AI opportunities.
Represent GM externally through publications, open-source contributions, patents, and participation in leading AI conferences.

Your Skills & Abilities (Required Qualifications)

PhD or equivalent in CS/EE
5+ years of experience in AI/ML research and applied development.
Deep expertise in modern ML architectures (transformers, generative AI, multimodal systems).
Proven track record of leading AI projects from research to production at scale.
Strong programming skills in Python and proficiency in one or more systems languages (C++/Go/Java).
Experience deploying AI systems on cloud-based GPUs/TPUs (AWS, Azure, GCP).
Recognized thought leader in the AI/ML community with demonstrated impact (research breakthroughs, patents, or widely adopted technologies).
Exceptional ability to mentor, influence, and collaborate across technical and business teams.

What Will Give You A Competitive Edge (Preferred Qualifications)

Demonstrated expertise in developing and training multimodal foundation models
Demonstrated research impact in AI/ML technologies either through important publications in first tier conferences or demonstrated contribution to industry leading systems.

This role is categorized as hybrid. This means the successful candidate is expected to report to the MTV office three times per week or any other frequency dictated by the business.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

The salary range for this role is 198,000 to 250,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.

Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Relocation: This job may be eligible for relocation benefits.

#Li-Cx1

About Gm

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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Job Summary

SGX is looking for a Machine Learning Engineer who is passionate about building scalable data/machine learning platforms and pioneering solutions. As a Machine Learning Engineer, you will play a crucial role in transforming how we run and deploy AI/ML models. Your work will directly impact our ability to build and deliver AI/ML use cases that will augment our users in their work or enable business opportunities. By enhancing our machine learning platform, you will enable us to make data-driven decisions and drive innovation across the organization. This is a 2-year contract role with an option for extension.

Job Responsibilities

Design and build scalable data platforms (including machine learning platforms) to support AI/GenAI use cases, streamline data storage, democratization, model deployment, and support feature engineering, model training, deployment, model monitoring and inference.
Develop and integrate data pipelines for continuous development, integration, testing, and scalable machine learning services.
Migrate existing data science projects to the new cloud machine learning platform.
Collaborate with data scientists and data engineers to design, implement, and integrate data pipelines.
Improve/automate existing model training, feature engineering, and evaluation pipelines, enabling the feedback loop of taking in labelled data from users/source systems for model re-training/tuning.
Design and develop CI/CD pipeline, consistent logging, tracking, and monitoring of pipelines and model performance to ensure consistent model performance and alert mechanisms for model drift.
Support data extraction and transformation for projects and users’ needs.
Review, support, improve, and run the platform, including the existing data platform/machine learning server, and environment management.
Provide support for data-related queries, extraction, and discrepancies.
Stay abreast of and analyze industry developments to identify areas of continuous improvement.

Job Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2-4 years of experience in setting up a machine learning platform, developing and deploying machine learning models and AI solutions.
Familiarity with machine learning platforms, LLM, Lang Chain.
Proficiency in Python, SQL, and modern AI/ML algorithms, with experience in deploying solutions into production. Experience with GCP/Vertex AI is a plus.
Highly driven, proactive, and a strong team player. Excellent interpersonal, written, and verbal communication skills in English. Ability to multitask effectively and handle large amounts of data.

","hiringOrganization":{"@type":"Organization","name":"SGX Group","sameAs":"https://www.sgx.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, SG","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":10,"item":{"@type":"JobPosting","title":"Computer Vision / Machine Learning Engineer","datePosted":"2025-09-22","description":"About the Role
We're looking for an experienced Computer Vision/Machine Learning Engineer to join our team, where you will apply your expertise to solve real-world computer vision problems. You'll play a key role in building, deploying, and integrating ML solutions into large-scale software systems, working collaboratively with all teams to help define the technical roadmap for our products. This position is ideal for someone who wants to work on critical software that has a real-world impact.\n

Responsibilities

Apply machine learning and computer vision techniques to add new analytical capabilities to our products, as well as enabling modern CV processing within our 3D reconstruction pipeline
Design, build, train, and experiment with ML models using PyTorch
Deploy ML models into production and integrate them into a large C++ codebase
Write and oversee code quality, testing, development standards, and best practices, ensuring robust, clean, and maintainable codebases
Work collaboratively with the Reveal team to define and execute the technical roadmap for current and future products
Contribute to technical documentation, design reviews, and code reviews to ensure maintainability and knowledge sharing
Stay up to date with the latest research and industry trends in CV, ML, and 3D data processing, applying relevant advancements where appropriate
Debug, identify root causes, and implement and test fixes for problems
Develop technical materials from conceptual ideas

Requirements

3-5 years of experience applying machine learning to solve real-world computer vision problems
Must be eligible to obtain and maintain a U.S. Top Secret security clearance
Deep understanding of computer vision fundamentals, including classical and ML-based approaches
Experience building, training, and experimenting with models using PyTorch
Experience deploying ML models to production environments
Familiarity with the ONNX framework
Experience with and willingness to work on software implementation and integration of ML solutions into large codebases
Experience with C++ and Python development in Linux or other command-line-based environments
Solid understanding of linear algebra
Ability to quickly understand and navigate complex systems and established codebases
Familiarity with representations of 3D data, such as point clouds, polygonal meshes, and depth maps, and algorithms for generating and processing them
Ability to quickly understand and navigate complex systems and established code bases
A desire to work on critical software that has a real-world impact

Nice To Haves

Working knowledge of classical 3D Computer Vision concepts such as camera models, stereo vision, camera calibration, SfM, SLAM
Familiarity with modern 3D CV advancements such as neural rendering techniques (NERFs, Gaussian Splatting), and related approaches for 3D reconstruction and scene representation
Experience building software solutions involving significant amounts of data processing and analysis

Compensation

Salary + Equity
Salary is determined by the applicant's experience, knowledge, skills, abilities, internal equity, and alignment with market data.

Benefits

Medical, Dental, Vision coverage
HSA/FSA options
Parental Leave
401(k): 200% match for the first 6% contributed
Unlimited Paid Time Off
Home Office Stipend

About Reveal TechnologyFounded in 2019, Reveal is a dynamic startup revolutionizing field operations by providing software tools and insights to individuals in remote, disconnected, and extreme environments. Our products include Farsight, a 3D processing and mission planning tool, and Identifi, which enables secure and rapid identity verification. Reveal is deeply committed to supporting defense, security, and safety missions. Having recently closed a $30M Series B funding round, we're growing our team to meet expanding demands and opportunities.
This position will be open on or our website until it is successfully filled. To submit your application, please click the “Apply” button and follow the steps as directed.
Proof of identity and eligibility to work in the United States is required for all hires.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Note: This job posting is intended for direct applicants only. We do not accept any unsolicited applications and request no outside recruiters contact us regarding this role.","hiringOrganization":{"@type":"Organization","name":"Reveal Technology","sameAs":"https://www.revealtech.ai"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":11,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (Modeling), Risk","datePosted":"2025-09-22","description":"

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.

\n\n

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

Machine Learning is an integral part of how we at Cash App design products, operate, and pursue our mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use ML and AI methods to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day.

As part of the Risk ML team, you will build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal to analyse emerging fraud patterns, engineer new features for risk models, and deploy robust models to take action on bad activity in real time.

This role can work remotely from anywhere in Australia or New Zealand, or from our offices in Melbourne, Sydney and Auckland.

You Will

Be responsible for building machine learning models to detect and act against fraudulent activity, as well as researching emerging fraud patterns, and leading and participating in cross-functional initiatives to tackle problems.
Collaborate cross-functionally with our engineering, product, and operations teams located across Australia and the United States (particularly Melbourne and San Francisco) to keep our customers and their money safe.
Work closely with the ML Engineering teams who build the systems that allow our models to operate at scale and in real time.
Contribute to the growth of our modelling capabilities through mentoring and supporting fellow modellers
Exercise a high level of autonomy and responsibility, own your solutions from design through to operation

You Have

Bachelor's degree in a quantitative field such as Mathematics/Statistics/Physics or Machine Learning. Masters or PhD preferred
3+ years of experience in machine learning, artificial intelligence, or a related field
Strong knowledge of machine learning algorithms and data analysis techniques
Excellent problem-solving skills and attention to detail
Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders

Technologies We Use And Teach

Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
MySQL, Snowflake, Tableau, Mode
GCP/AWS

Use of AI in Our Hiring Process

We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws.

Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.

Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone.

Privacy Policy

","hiringOrganization":{"@type":"Organization","name":"Block","sameAs":"https://block.xyz/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Melbourne, Australia","addressCountry":"Australia","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":12,"item":{"@type":"JobPosting","title":"Co-op - Machine Learning Engineer (Spanish/Portuguese)","datePosted":"2025-09-22","description":"At Lendbuzz, we believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, we’ve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.
We are seeking an enthusiastic Machine Learning Co-op to join our team, focusing on our sales and collection AI chatbot projects within our Language Understanding and Semantic Analysis group. Ideal candidates should be proficient in Spanish or Portuguese, eager to explore the intricacies of the auto loan industry, and interested in building real-world applications of Large Language Models (LLMs). You will gain hands-on experience with large-scale data annotation, data cleaning, multilingual model evaluation, and product design.\n

Key Responsibilities:

Annotate chat data from sales-dealers and customers to train AI chatbots
Develop and refine prompts and Retrieval-Augmented Generation (RAG) technique cvg cant es to enhance the performance of zero-shot and few-shot language models (LLMs)
Assess the needs of dealers and customers, and implement AI chatbot functionalities to address those needs
Fine-tune language models as time permits and based on the availability of annotated data

Requirements:

Proficiency in either Spanish or Portuguese (spoken and written) is required
Pursuing a Bachelor’s degree in Computer Science or a related field, pursuing a M.S in Computer Science or a related field preferred (graduation date of December 2026 or later)
Coursework or experience in Data Structures, Algorithms, Linear Algebra, Probability, and foundational Machine Learning and Artificial Intelligence concepts
Familiarity with Python and its data analysis libraries
Strong grasp of core CS and ML concepts
Interview process will include questions on coursework, coding, probability, machine learning, and Linux fundamentals
Able to work 3-4 days in our downtown Boston office full time from January-August 2026

We believe:
Diversity is a competitive advantage. We celebrate our differences, and are better when we have a variety of experiences, viewpoints, and backgrounds.
Compassion is a strength. We care about our customers and look to build long-term relationships with them.
Simplicity is a key feature. We work hard to make our forms and processes as painless and intuitive as possible.
Honesty and transparency are non negotiable. We incorporate these traits in all of our interactions.
Financial opportunity belongs to everyone. We work every day to improve lives by extending this opportunity.
If you believe these things too then we would love to hear from you!","hiringOrganization":{"@type":"Organization","name":"Lendbuzz","sameAs":"https://www.lendbuzz.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, MA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":13,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, AI Decisioning","datePosted":"2025-09-22","description":"

About Hightouch

Hightouch’s mission is to empower everyone to take action on their data. Hundreds of companies, including Autotrader, Calendly, Cars.com, Monday.com, and PetSmart, trust Hightouch to power their growth.

We pioneered the Composable Customer Data Platform (CDP), which lets companies use their own data warehouse to collect, prepare, and activate customer data for marketing personalization and business operations. Our new AI Decisioning platform goes a step further, allowing marketers to set goals and guardrails that AI agents can then use to personalize 1:1 customer interactions. Traditionally, only technical teams had the skills to access and use customer data. With Hightouch, every business user can deliver personalized customer experiences, optimize performance marketing, and move faster by leveraging data and AI across their organization.

Our team focuses on making a meaningful impact for our customers. We approach challenges with a first-principles mindset, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

What else? We’re based in San Francisco but have team members all over the world. Our Series C put us at a $1.2B valuation, and we are backed by leading investors such as Sapphire Ventures, Amplify Partners, ICONIQ Growth, Bain Capital Ventures, Y-Combinator, and Afore Capital.

About The Role

We’re looking to hire a machine learning engineer as we expand our data activation products to include an intelligence layer. While hundreds of companies use Hightouch today to sync data into their SaaS systems to automate and improve operations, there’s a lot of surface area we haven’t touched in helping companies figuring out which customers to message, what content to put in messages, and when to send messages. A lot of this work today is done manually through intuition and guesswork, and we believe that adding machine learning could have a step function impact for our customers. And given our access to data warehouses and databases, Hightouch is perfectly placed to make use of a company’s customer data in building a powerful intelligence layer.

Some of the problems we’ll be working on include:

Personalization and Product Recommendation: There are often many options for what content a company could message a user with, including which products to show from catalogues. Given this large state space, how can Hightouch help personalize messages with the most relevant content for each user?
Automated Experimentation: Helping companies intelligently navigate and automate experiments across the extensive number of options for messaging customers.
Predictive Audiences: Building models to predict which users are most likely to convert, churn, or take desired actions.
Content Generation: Particularly with recent advances in LLMs, how can we help marketers generate text, images, and creatives that are compelling to their customers?
Budget Optimization: Helping companies assess which marketing spend is driving the most incremental conversions, and where the marginal CAC is lowest.

As an early machine learning engineer, you will help build comprehensive solutions to the above domains from scratch. Responsibilities will be highly varied and include working on customer research, problem definition, predictive modeling, machine learning infrastructure, and partnering with customers.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $200,000 - $260,000 USD per year, which is location independent in accordance with our remote-first policy.

Interview Process

Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense, ability to architect backend and distributed systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.

Intro Call [15-30m]: Introductory call with either a member of our recruiting team or the hiring manager to get to know each other and see if the role could be a good mutual fit.
System Design Screen [45m]: Designing a data processing feature end-to-end.
Machine Learning Modeling Interview [90m]: Designing a predictive model end-to-end, including data collection and preparation, model training and evaluation, and what systems would be needed to run the model in production.
System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.
Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.

","hiringOrganization":{"@type":"Organization","name":"Hightouch","sameAs":"https://hightouch.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote (North America)"}}}},{"@type":"ListItem","position":14,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - New Grad 2026","datePosted":"2025-09-22","description":"

#Teamnextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com.

Meet Your Future Neighbors

At Nextdoor, Machine Learning is one of the most critical teams we are growing. ML is transforming our product through personalization, driving significant impact across various platform components, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great machine learning engineers who believe in the power of the local community to empower our members to make their communities great places to live.

At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in-office presence and work-from-home experience for our valued employees.

The Impact You’Ll Make

You will be part of an avid and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis.

Build and iterate on ML-driven products to foster creativity, discovery, and engagement on Nextdoor
Develop personalized content and user recommendation systems that millions of users rely on daily
Run and analyze live user-facing experiments to iterate on model quality
Collaborate with other engineers and data scientists to create optimal experiences on the platform
Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises
Build in-person relationships with team members and contribute to Nextdoor’s company culture

We have MLE positions across multiple tracks, including Feed, Notifications, Ads, Network Growth, Knowledge Graph, and ML Platform.

What You’Ll Bring To The Team

Master’s Degree or Ph.D. in Computer Science, Applied Math, Statistics, or a related field, graduating in December 2025
Deep understanding of machine learning concepts (e.g. deep learning) and applications (e.g. recommender systems, knowledge graph)
Internship in machine learning engineering in a related field (e.g. social networking, e-commerce)
Strong programming skills in Python or Java
Effective communication and collaboration skills
Passion for Nextdoor’s mission and purpose
Bonus Points - Industry experience of applying machine learning at scale
Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done

Rewards

Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography.

The starting salary for this role is expected to be $150,000 to $175,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role.

We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date.

Perks & Benefits

We’ve got you covered! We are dedicated to supporting your personal and professional growth with a comprehensive benefits package that includes:

Access to benefits (including mental health benefits, commuter benefits, wellness benefits, gender affirming care, etc)
Flexible paid time off
Dedicated volunteer days
Stocked micro-kitchens and lunches at our offices
Ability to join any of our Employee Resource Groups (ERGs)

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.

","hiringOrganization":{"@type":"Organization","name":"Nextdoor","sameAs":"https://about.nextdoor.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas, TX","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":15,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-22","description":"

Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery.

\n\n

As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy.

\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.

\n\n\n

About Thoughtworks

\n\n

Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.

\n\n

#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Quito","addressCountry":"Ecuador","addressRegion":"South America"}}}},{"@type":"ListItem","position":16,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-22","description":"

\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

\n\n\n

About Thoughtworks

\n\n

#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Lima","addressCountry":"Peru","addressRegion":"South America"}}}},{"@type":"ListItem","position":17,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-22","description":"

\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

\n\n\n

About Thoughtworks

\n\n

#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Santiago","addressCountry":"Chile","addressRegion":"South America"}}}},{"@type":"ListItem","position":18,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

The opportunity
At Unity, we’re committed to building a culture that fosters collaboration and innovation. Within our fast-paced environment, we’re tackling complex challenges that drive meaningful impact for creators and users across our ecosystem.

Our Foundation Modeling team plays a central role in this effort by developing state-of-the-art conversion rate (CVR) prediction and market price models that power our ad ranking and recommendation systems. These models help advertisers reach the right users at the right time by accurately estimating engagement and conversion likelihood. By leveraging large-scale behavioral data, creative features, and contextual signals, we continuously improve the relevance and accuracy of our predictions. This drives key outcomes such as higher user engagement, stronger conversion performance, and better return on ad spend — enabling advertisers to achieve their goals while delivering a better experience for users.

We are seeking a highly skilled Senior ML Engineer to drive state-of-the-art bidding optimization systems that enable efficient budget pacing, goal-aligned automated strategies, continual improvement through experimentation, and sustainable growth for Unity Ads.

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, 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 CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International 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.

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

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$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":19,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, 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 CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International 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

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$165,600—$248,400 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":20,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, 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 CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International 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$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":21,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, 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 CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International 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$165,600—$248,400 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":22,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-22","description":"

Machine Learning Engineer

About Rent the Runway

Founded in 2009, Rent the Runway is disrupting the trillion-dollar fashion industry and changing the way women get dressed through the Closet in the Cloud, the world’s first and largest shared designer closet. RTR’s mission has remained the same since its founding: powering women to feel their best every day. Through RTR, customers can subscribe, rent items a-la-carte and shop resale from hundreds of designer brands. The Closet in the Cloud offers a wide assortment of millions of items for every occasion, from evening wear and accessories to ready-to-wear, workwear, denim, casual, maternity, outerwear, blouses, knitwear, loungewear, jewellery, handbags, activewear, ski wear, home goods and kidswear. RTR has built a two-sided discovery engine, which connects deeply engaged customers and differentiated brand partners on a powerful platform built around its brand, data, logistics and technology. Under CEO and Co-Founder Jennifer Hyman’s leadership, RTR has been named to CNBC’s “Disruptor 50” five times in ten years, and has been placed on Fast Company’s Most Innovative Companies list four times, while Hyman herself has been named to the “TIME 100: Most Influential People in the World\" and as one of People Magazine’s “Women Changing the World.”

Galway Office

Rent The Runway established its European Technology Hub in Galway in April 2019. Based in the historic Claddagh area of the city, the growing team in Galway tackles core technology challenges and influences the next generation of services critical to Rent The Runway’s success and continued growth.

The Galway office is Rent the Runway's first international office outside the US and enables the company to significantly expand its Software Engineering, Product Development, Machine Learning Engineering and Data Science footprint. Rent The Runway’s Galway-based employees have the opportunity to grow their careers across several roles and career paths in Technology.

Our engineering team is smart, pragmatic, and entrepreneurial. We practice continuous integration & test-driven development, engage in constant peer code reviews & pair programming, and work hard to give back to the software community through open-source contributions.

About The Role:

Machine Learning Engineers at Rent the Runway create data products that have tangible effects on our customer experience and internal operations. You will own projects end to end, from framing which problems to tackle through transforming information from our massive data ecosystem into actionable insights, and ultimately building & integrating algorithms into our network of services in collaboration with our product & software engineering teams.

You will have the opportunity to impact all parts of our business: determining what inventory assortment to buy, optimizing the lifespan of that inventory, establishing the right network of warehouses & transportation methods to best serve our customers, personalizing the user experience, optimizing user acquisition & retention, investigating how we can improve customer service by serving the right information at the right time, optimally pricing clothing rentals and sales, forecasting demand and more.

We are always interested in speaking with developing and experienced Machine Learning engineers interested in joining our team. If that’s you, read on for a snapshot of the type of work our Machine Learning engineers do across our various teams, share your details and a member of our Talent team will be in touch!

What You’Ll Do:

Work on a team of peers in an environment that will keep you constantly challenged and learning new things every day.
Develop and deploy performant algorithms powering customer-facing applications that are core to our business and success.
Collaborate closely in an equal partnership with our business, product and engineering teams.
Have a significant voice both in what you work on and how the work is carried out.

About You:

3+ years work experience building data products, preferably with Python, and integrating them into internal and customer-facing applications in production environments. Bonus points if you’ve: built & maintained services using AWS, GCP; deployed & maintained production deep learning models using frameworks such as Tensorflow, PyTorch, Keras in a business environment.
Ability and desire to own your project through its entire lifecycle, from data exploration and analysis to modelling, experimentation, production implementation, monitoring, and communication with stakeholders.
Experience transforming vague problems into algorithmic solutions
Desire to drive serious business impact and a bias to action. You like to move fast, you follow through, and you’re accountable to the results.
Owner’s mindset. No job is too big or too small, and you always leave things better than you found them.
An innate curiosity and an open mind.

Benefits:

At Rent the Runway, we’re committed to the happiness and wellbeing of our employees, and aim to create a workplace that fosters both personal and professional growth. Our inclusive benefits include, but are not limited to:

Generous Paid Time Off including annual leave, paid bereavement, and family sick leave - every employee needs time to take care of themselves and their family.
Universal Paid Parental Leave for both parents + flexible return to work program - because we know your newest family member(s) deserve your undivided attention.
Paid Sabbatical after 5 years of continuous service - unplug, recharge, and have some fun.
Competitive Stakeholder Pension - taking care of your future.
Comprehensive health, dental care and dependents care from day 1 of employment - Your health comes first and we’ve got you covered.
Company wide events and outings - our team spirit is no joke - we know how to have fun!
Hybrid Work - This is a hybrid role based in our Galway, Ireland office. Employees have to option to work remotely 2-3 days per week.

Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee on any legally-recognised basis, including, but not limited to: gender, marital status, family status, age disability, sexual orientation, race, religion, and membership of the Traveller community.

#Li-Em1

By submitting your application below, you agree that you have read and acknowledge Rent the Runway's Candidate Privacy Policy, found here.

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We are seeking a highly skilled Staff ML Engineer to drive state-of-the-art bidding optimization systems that enable efficient budget pacing, goal-aligned automated strategies, continual improvement through experimentation, and sustainable growth for Unity Ads.

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International relocation support is not available for this position.
Work visa/immigration sponsorship 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":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":24,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International relocation support is not available for this position.
Work visa/immigration sponsorship 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":25,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International relocation support is not available for this position.
Work visa/immigration sponsorship 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-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":26,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
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.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like 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

International relocation support is not available for this position.
Work visa/immigration sponsorship 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":27,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Intern, Agentic ML (Summer 2026)","datePosted":"2025-09-22","description":"

Join Us In Building The Future Of Finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About The Team + Role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Agentic team at Robinhood is building the foundation for AI agents that power the next generation of AI financial products and internal tools. Our mission is to empower teams across the company to rapidly build, evaluate, and deploy high-performance AI agents through intuitive tooling, production-grade infrastructure, and continuous optimization support. We’re creating a platform that makes it easy for engineers to experiment, ship, and scale agents reliably.

We’re looking for a passionate and curious Machine Learning Intern to join us in advancing this mission and learning alongside a world-class team of ML engineers.

What You’Ll Do

Build and prototype tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead.
Assist in building platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains.
Maintain feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior.
Support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring.
Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems.

What You Bring

Pursuing a degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field, with an expected graduation date in Winter 2026 or Spring 2027.
Solid foundation in software engineering, machine learning principles, algorithms, and data structures.
Familiarity with Python and basic ML frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
Interest in building agentic systems and large language models.
A collaborative mindset and strong communication skills.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected hourly range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$48—$48 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$42—$42 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$37—$37 USD

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

","hiringOrganization":{"@type":"Organization","name":"Robinhood","sameAs":"https://robinhood.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":28,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Intern, Applied ML (Summer 2026)","datePosted":"2025-09-22","description":"

Join Us In Building The Future Of Finance.

About The Team + Role

The mission of the Applied Machine Learning team is to develop scalable, data- and model-driven solutions that enhance decision-making across Robinhood. We focus on personalizing user experiences, helping customers discover and engage with the most valuable products and features. To empower ML adoption company-wide, we’re also building accessible model development tools that democratize machine learning at Robinhood.

We’re looking for a passionate and curious Machine Learning Intern to join us in advancing this mission and learning alongside a world-class team of ML engineers.

What You’Ll Do

Build and Prototype ML Models: Work on early-stage ranking, recommendation, and personalization models using techniques like collaborative filtering, content-based filtering, or learning-to-rank approaches.
Experimentation & Evaluation: Assist in setting up and analyzing A/B tests and offline experiments to evaluate the effectiveness of ML algorithms.
Explore and Analyze Data: Dive into rich datasets to extract signals and support data-driven feature engineering and model tuning.
Collaborate Cross-Functionally: Work with engineers, data scientists, and product managers to understand business needs and help integrate ML into real product use cases.
Contribute to Internal Tools: Help improve model development tools, document findings, and support reusable libraries that enable broader adoption of ML practices.

What You Bring

Pursuing a degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field, with an expected graduation date in Winter 2026 or Spring 2027.
Solid foundation in machine learning principles, algorithms, and data structures.
Familiarity with Python and basic ML frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
Interest in recommendation systems, personalization, or reinforcement learning.
Enthusiasm for working with large datasets and running experiments to learn what works.
A collaborative mindset and strong communication skills.

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

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Our Engineering community is growing, and we’re now looking for a Senior ML Engineer - Databricks (m/f/*) to join our team in Nepal, supporting our global growth.

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As a Senior Machine Learning Engineer (m/f/*), you will lead the design and implementation of advanced data and AI solutions on the Databricks Lakehouse Platform. Your focus will lie in building robust ML pipelines, enabling GenAI capabilities, and delivering production-grade solutions that support data-driven innovation at scale.

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What We Offer

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A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
Contribute your ideas to our unique projects and make an impact by turning them into reality
Balance your work and personal life through our workflow organization and decide yourself if you work at home, in the office, or on a hybrid setup
Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
Individual development plan, professional development opportunities
Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
Local, virtual, and global team events, in which UT colleagues become acquainted with one another

\n\n\n

What You’Ll Do

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Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform using Spark, Delta Lake, and MLflow.
Perform exploratory data analysis (EDA), data cleaning, feature engineering, and model evaluation to support data-driven use cases.
Collaborate with data engineers and business stakeholders to translate real-world problems into ML solutions.
Deploy models using MLflow, manage model versioning, and set up monitoring and retraining strategies.
Optimize the performance and cost-efficiency of ML workloads on Databricks clusters.
Apply best practices in MLOps, ensuring reproducibility, governance, and scalability of ML solutions.
Guide and mentor team members on Databricks, ML engineering best practices

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What You’Ll Bring

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Hands-on experience with Databricks (on Azure, AWS, or GCP), especially Spark (PySpark or Scala), Delta Lake, and MLflow.
Deep understanding of the machine learning lifecycle, including data prep, modeling, evaluation, and deployment.
Proficiency in Python, with solid foundations in ML libraries (e.g., scikit-learn, pandas).
Experience building production-ready ML pipelines and working with large-scale datasets.
Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and version control (Git/GitHub).
Strong problem-solving and communication skills, with the ability to explain complex models and logic to stakeholders.
Fluent English communication skills (written and spoken).

Nice To Have

Experience with MLOps workflows: model monitoring, automated retraining, A/B testing.
Exposure to cloud-native architectures, CI/CD for ML, and infrastructure-as-code (e.g., Terraform).
Knowledge of Databricks Unity Catalog for model governance and security.
Experience working in regulated or enterprise data environments.

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Did we pique your interest, or do you have any questions?

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We want to hear from you: contact us at recruit@ultratendency.com

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About Us

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Ultra Tendency is an international premier Data Engineering consultancy for Big Data, Cloud, Streaming, IIoT and Microservices. We design, build, and operate large-scale data-driven applications for major enterprises such as the European Central Bank, HUK-Coburg, Deutsche Telekom, and Europe’s largest car manufacturer. Founded in Germany in 2010, UT has developed a reliable client base and now runs 8 branches in 7 countries across 3 continents.

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We do more than just leverage tech, we build it. At Ultra Tendency we contribute source code to +20 open-source projects including Ansible, Terraform, NiFi, and Kafka. Our impact on tech and business is there for anyone to see. Enterprises seek out Ultra Tendency because we solve the problems others cannot.

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We love the challenge: together, we tackle diverse and unique projects you will find nowhere else. In our knowledge community, you will be a part of a supportive network, not a hierarchy. Constant learning and feedback are our drivers for stable development. With us you can develop your individual career through work-life balance.

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We evaluate your application based on your skills and corresponding business requirements. Ultra Tendency welcomes applications from qualified candidates regardless of race, ethnicity, national or social origin, disability, sex, sexual orientation, or age.

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Data privacy statement: Data Protection for Applicants – Ultra Tendency

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Our Engineering community is growing, and we’re now looking for a Senior ML Engineer - Databricks (m/f/*), to join our team in Germany, supporting our global growth.

\n\n\n

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

What We Offer

\n\n\n

A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
Contribute your ideas to our unique projects and make an impact by turning them into reality
Balance your work and personal life through our workflow organization and decide yourself if you work at home, in the office, or on a hybrid setup
Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
Individual development plan, professional development opportunities
Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
Local, virtual, and global team events, in which UT colleagues become acquainted with one another

\n\n\n

What You’Ll Do

\n\n

Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform using Spark, Delta Lake, and MLflow.
Perform exploratory data analysis (EDA), data cleaning, feature engineering, and model evaluation to support data-driven use cases.
Collaborate with data engineers and business stakeholders to translate real-world problems into ML solutions.
Deploy models using MLflow, manage model versioning, and set up monitoring and retraining strategies.
Optimize the performance and cost-efficiency of ML workloads on Databricks clusters.
Apply best practices in MLOps, ensuring reproducibility, governance, and scalability of ML solutions.
Guide and mentor team members on Databricks, ML engineering best practices

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

What You’Ll Bring

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Hands-on experience with Databricks (on Azure, AWS, or GCP), especially Spark (PySpark or Scala), Delta Lake, and MLflow.
Deep understanding of the machine learning lifecycle, including data prep, modeling, evaluation, and deployment.
Proficiency in Python, with solid foundations in ML libraries (e.g., scikit-learn, pandas).
Experience building production-ready ML pipelines and working with large-scale datasets.
Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and version control (Git/GitHub).
Strong problem-solving and communication skills, with the ability to explain complex models and logic to stakeholders.
Fluent German & English communication skills (written and spoken).

Nice To Have

Experience with MLOps workflows: model monitoring, automated retraining, A/B testing.
Exposure to cloud-native architectures, CI/CD for ML, and infrastructure-as-code (e.g., Terraform).
Knowledge of Databricks Unity Catalog for model governance and security.
Experience working in regulated or enterprise data environments.

\n\n\n

Did we pique your interest, or do you have any questions?

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We want to hear from you: contact us at recruit@ultratendency.com

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About Us

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Data privacy statement: Data Protection for Applicants – Ultra Tendency

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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: Work on various machine learning challenges to build systems and machine learning models to improve the experience for both Pinners and creators on Pinterest at scale. Apply the latest advances in deep learning and machine learning to personalize Pinterest users' experience. Develop new features to improve Pinterest's user and pin understanding in models. Impact 450M+ monthly active users by developing the next generation of discovery technologies. Work in a fast-paced machine learning environment with quick experimentation and product launches. 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 two (2) years of experience in the job offered or in any occupation in related field.

Special Skill Requirements: (1) Python; (2) Java; (3) C++; (4) PySpark; (5) PyTorch; (6) CUDA; (7) TensorFlow; (8) Spark; (9) Hadoop; (10) Machine Learning. Any suitable combination of education, training and/or experience is acceptable. Telecommuting is permitted.

Salary: $168,840.00 - $222,695.00 per annum
Reference #: L23-144289
This position is not available for relocation assistance.

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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$168,840—$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":"New York, NY, US; Remote, NY, US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":32,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, Risk Data Mining - USDS","datePosted":"2025-09-22","description":"The USDS-Platform and Community Integrity (PaCI) team is missioned to:
\n- Protect U.S. TikTok users, including and beyond content consumers, creators, advertisers;
\n- Secure platform health and community experience authenticity;
\n- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.
\n
\nThe PaCI team works to minimize the damage of inauthentic behaviors on TikTok platforms, covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti-spam, API abuse, growth fraud, live streaming security and financial safety, etc. In this team, you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure, and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to make quick and solid differences.
\n
\nIn order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
\n
\nResponsibilities:
\n- Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
\n- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
\n- Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose, California, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":33,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Databricks (m/f/*)","datePosted":"2025-09-22","description":"

Our Engineering community is growing, and we’re now looking for a Senior ML Engineer - Databricks, to join our team in Spain, supporting our global growth.

\n\n\n

As a Senior Machine Learning Engineer, you will lead the design and implementation of advanced data and AI solutions on the Databricks Lakehouse Platform. Your focus will lie in building robust ML pipelines, enabling GenAI capabilities, and delivering production-grade solutions that support data-driven innovation at scale.

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

What We Offer

\n\n\n

A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
Contribute your ideas to our unique projects and make an impact by turning them into reality
Balance your work and personal life through our workflow organization and decide yourself if you work at home, in the office, or on a hybrid setup
Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
Individual development plan, professional development opportunities
Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
Local, virtual, and global team events, in which UT colleagues become acquainted with one another

\n\n\n

What You’Ll Do

\n\n

Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform using Spark, Delta Lake, and MLflow.
Perform exploratory data analysis (EDA), data cleaning, feature engineering, and model evaluation to support data-driven use cases.
Collaborate with data engineers and business stakeholders to translate real-world problems into ML solutions.
Deploy models using MLflow, manage model versioning, and set up monitoring and retraining strategies.
Optimize the performance and cost-efficiency of ML workloads on Databricks clusters.
Apply best practices in MLOps, ensuring reproducibility, governance, and scalability of ML solutions.
Guide and mentor team members on Databricks, ML engineering best practices

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

What You’Ll Bring

\n\n\n

Hands-on experience with Databricks (on Azure, AWS, or GCP), especially Spark (PySpark or Scala), Delta Lake, and MLflow.
Deep understanding of the machine learning lifecycle, including data prep, modeling, evaluation, and deployment.
Proficiency in Python, with solid foundations in ML libraries (e.g., scikit-learn, pandas).
Experience building production-ready ML pipelines and working with large-scale datasets.
Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and version control (Git/GitHub).
Strong problem-solving and communication skills, with the ability to explain complex models and logic to stakeholders.
Fluent English communication skills (written and spoken).

Nice To Have

Experience with MLOps workflows: model monitoring, automated retraining, A/B testing.
Exposure to cloud-native architectures, CI/CD for ML, and infrastructure-as-code (e.g., Terraform).
Knowledge of Databricks Unity Catalog for model governance and security.
Experience working in regulated or enterprise data environments.

\n\n\n

Did we pique your interest, or do you have any questions?

\n\n\n

We want to hear from you: contact us at recruit@ultratendency.com

\n\n\n \n\n

About Us

\n\n\n

\n\n\n\n

\n\n\n

Data privacy statement: Data Protection for Applicants – Ultra Tendency

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Bedrijfsomschrijving

Sopra Steria is een Europese techpartner met meer dan 56.000 collega’s in 30 landen. We helpen organisaties met slimme, schaalbare softwareoplossingen. Technologie is het middel, mensen maken het verschil.

Je werkt in Groningen, vanuit de Data-practice van Sopra Steria Noord. Hier komen data scientists en engineers samen om oplossingen te bouwen die klanten vooruithelpen. Dat doen we voor organisaties in de publieke en private sector, op het snijvlak van AI, analytics en strategisch advies.

Naast de dataprofessionals werk je samen met collega’s uit teams als Strategy & Business Design, Product Management, Java, Microsoft, frontend en agile testing. Samen brengen we de brug tot stand tussen techniek en organisatie.

The world is how we shape it. Let’s shape it together.

Vacatureomschrijving

Als Machine Learning Engineer werk je niet met data om het data, maar om er echte waarde uit te halen. Jij weet: modellen bouwen is één ding, zorgen dat ze werken en blijven draaien in de praktijk, dat is waar het telt.

Je werkt aan projecten die ertoe doen. Van hypothese tot productie. Je ontwikkelt, test en implementeert ML-oplossingen die echt gebruikt worden.

Wat je onder andere gaat doen:

Je maakt ruwe data bruikbaar met slimme modellen, pipelines en visualisaties
Je zet hypotheses om in concrete experimenten
Je werkt met moderne ML-tools en cloudplatforms (Azure, AWS, GCP)
Je zorgt ervoor dat modellen niet op de plank blijven liggen, maar écht in productie draaien
Je denkt mee met klanten én ontwikkelteams om oplossingen schaalbaar, onderhoudbaar en impactvol te maken

Functie-Eisen

Je bent nieuwsgierig, analytisch en weet hoe je complexe modellen vertaalt naar iets wat klanten ook echt kunnen gebruiken. Je werkt graag samen met anderen, maar pakt ook zelfstandig je verantwoordelijkheid.

Wat Jij Meebrengt:

een masterdiploma of vergelijkbare ervaring binnen data science, machine learning of AI
ervaring met Python en SQL
kennis van cloudplatformen zoals Azure, AWS of GCP
ervaring met het bouwen én in productie brengen van modellen
affiniteit met thema’s als explainable AI, MLOps, anomaly detection of bijvoorbeeld NLP
je spreekt Nederlands op minimaal B2-niveau

Aanvullende Informatie

Dit krijg je van ons

Je krijgt de ruimte om je werk op jouw manier te doen. We vertrouwen op je expertise en zorgen dat je de juiste mensen en middelen om je heen hebt om te groeien.

Wat Je Kunt Verwachten:

je krijgt direct een vast contract met een goed salaris
een mobiliteitsbudget of leaseauto die past bij jouw manier van reizen
een laptop, telefoon en thuiswerkbudget zodat je ook thuis goed uitgerust bent
27 vakantiedagen (waarvan 7 via het Flex Benefits-budget), met de mogelijkheid om bij te kopen tot 40 dagen
een goede pensioenregeling en collectieve zorgverzekering
toegang tot meer dan 250 trainingen via de Sopra Steria Academy
de kans om je te laten inspireren via meetups, kennissessies en events binnen en buiten je vakgebied
en leuke uitjes met je team, van game nights tot een dagje Efteling

Je sluit je aan bij de Data-practice binnen Area Noord. Een team waar kennisdelen vanzelf gaat, inhoud voorop staat en waar je samenwerkt met collega’s uit verschillende expertises.

Lijkt deze job iets voor jou?
Ben je klaar om met ons de wereld vorm te geven? Mooi. We kijken uit naar je sollicitatie.

______

Sopra Steria is een werkgever die gelijke kansen biedt. Alle gekwalificeerde sollicitanten worden in aanmerking genomen voor een job zonder rekening te houden met leeftijd, afkomst, nationaliteit, huidskleur, verlof voor familie- of medische zorg, geslachtsidentiteit of -uitdrukking, genetische informatie, immigratiestatus, burgerlijke staat, medische toestand, nationale herkomst, fysieke of mentale handicap, politieke voorkeur, beschermde veteranen- of militaire status, ras, etniciteit, religie, geslacht (inclusief zwangerschap), seksuele geaardheid of enig ander kenmerk dat wordt beschermd door toepasselijke lokale wetten, voorschriften en verordeningen. We koesteren een werkomgeving die inclusief is en alle verschillen respecteert.

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Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Job Description

The Generative AI Centre of Expertise (GenAI CoE) at Experian exists to improve our products, our internal processes and our day-to-day work through GenAI and process automation. The team is a mix of ML engineers, data scientists and product owners, who are dedicated to the next wave of innovation using GenAI.

Who is a ML Engineer?

In the GenAI CoE, ML Engineers drive the delivery of concepts and proven ideas into products and services that Experian can take to their customers, whether that be businesses or direct to consumers. To do this, we build upon the outcomes of our experiments to meet the product requirements - considering performance, maintainability, and scalability. We, alongside the data scientists in the team, collaborate with a range of stakeholders.

You Will:

Partner with teams across the organisation to design and build GenAI solutions—from early experimentation to full-scale production—potentially including DevOps work where needed.
Architect and build high-performant solutions, which may involve traditional ML modelling and/or large datasets, as well as GenAI.
Discover and introduce new technologies to the team, staying up to date with the latest approaches that enable the next generation of Experian’s products with GenAI and ML.
Learn quickly and be able to put new GenAI concepts into practice.
Spend 10% of your work time on continuous learning and sharing expertise on generative-AI technologies.

You

Have experience in Python.
Are a self-starter with strong troubleshooting skills.

It would be fantastic if you also have:

Have a degree or equivalent qualification in a STEM subject.
Are familiar with Unix environments.
Exposure to at least one other programming language besides Python.
Proficiency in object-oriented programming (OOP), SOLID principles, and test-driven development (TDD).
Proficiency with Docker and experience working with container orchestration tools such as Kubernetes, Docker Swarm, or cloud-based alternatives.
Comfort working across the full development stack, especially for prototyping.
Passion for applying GenAI and machine learning across diverse domains and throughout the full project lifecycle.
Conceptual understanding of common ML approaches (e.g., LLMs, GBMs, deep learning) and typical software architectures.
Detailed-oriented, pragmatic, and collaborative team player.
Experience as a lead developer tackling complex problems at scale.
Experience mentoring junior engineers.
Familiarity with various machine learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow).
Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs).
Have experience with cloud computing platforms.
Greater familiarity with AWS compared to other cloud computing platforms.
Have experience developing REST APIs.

Qualifications

Have experience in Python
Are a self-starter with strong troubleshooting skills

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

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At CarTrawler, you’ll find more than just a job. You’ll find flexibility, meaningful impact, and a culture built by the people who live it every day. Our culture is built on high performance, genuine connection, and a shared commitment to making an impact, without sacrificing personal wellbeing. With flexible working models, meaningful time off, and dedicated growth opportunities, we enable people to do great work and feel good doing it.
We have a hybrid working policy with two mandatory days a week in our Dublin office, you have the freedom to design a routine that supports your productivity and personal life. The office offers ample car parking, a heavily subsidized (KC Peaches) canteen, convenient proximity to the Luas, and access to EV charging stations.
\n

Role Purpose

Support the development and maintenance of software tools that underpin Data Science solutions and operations, using modern technologies (e.g. AWS, Docker, Kubernetes) to contribute to improved business performance.
Collaborate with business stakeholders and engineering teams to gather requirements and contribute to the design and implementation of solutions.
Assist in maintaining and enhancing existing tools/services developed by the Data Science team.
Build CI/CD pipelines and contribute to testing, logging, and monitoring processes under guidance.
Participate in code reviews and follow CarTrawler best practices for clean, maintainable code.
Continuously develop technical skills and support the wider team, working under the mentorship of senior engineers.

Responsibilities & Accountabilities

Undergraduate degree in Computer Science, Engineering, Mathematics, or related technical field, or relevant internship/industry experience.
Good understanding of software engineering and DevOps practices (e.g. Jenkins, Github Actions), including Object-Oriented Programming, data structures, version control, REST APIs, and containerisation tools (e.g. Docker, Kubernetes).
Exposure to cloud platforms such as AWS or Azure.
Experience with developing GenAI applications, or surrounding tech stack (e,g. Vector DB, NLP, LLM) seen as a plus.
Proficient in writing clean, structured Python code; familiarity with common Python libraries used in data science and machine learning.
Comfortable using version control systems (e.g. Git) and basic development workflows (commits, branches, pull requests).
Exposure to ML libraries (e.g. scikit-learn; bonus for familiarity with TensorFlow or PyTorch).
Willingness to learn test-driven development and build basic unit and integration tests with support.
An interest in learning about production considerations like resource constraints and scalability.
Basic SQL skills; exposure to other database types (graph, NoSQL) is a plus.
Strong communication skills with a desire to learn how to present technical concepts clearly to varied audiences.
A proactive and curious mindset, with a collaborative approach to learning and team engagement.
Experience with developing GenAI applications or of supporting tech stack seen as a plus

Skills & Experience Required

Undergraduate degree in Computer Science, Engineering, Mathematics, or related technical field, or relevant internship/industry experience.
Good understanding of software engineering and DevOps practices (e.g. Jenkins, Github Actions), including Object-Oriented Programming, data structures, version control, REST APIs, and containerisation tools (e.g. Docker, Kubernetes).
Exposure to cloud platforms such as AWS or Azure.
Experience with developing GenAI applications, or surrounding tech stack (e,g. Vector DB, NLP, LLM) seen as a plus.
Proficient in writing clean, structured Python code; familiarity with common Python libraries used in data science and machine learning.
Comfortable using version control systems (e.g. Git) and basic development workflows (commits, branches, pull requests).
Exposure to ML libraries (e.g. scikit-learn; bonus for familiarity with TensorFlow or PyTorch).
Willingness to learn test-driven development and build basic unit and integration tests with support.
An interest in learning about production considerations like resource constraints and scalability.
Basic SQL skills; exposure to other database types (graph, NoSQL) is a plus.
Strong communication skills with a desire to learn how to present technical concepts clearly to varied audiences.
A proactive and curious mindset, with a collaborative approach to learning and team engagement.
Experience with developing GenAI applications or of supporting tech stack seen as a plus

Employee Benefits

Financial: Annual Bonus, Pension Scheme, Income Protection, Life Assurance
Lifestyle & Working: Subsidized Canteen, Flexible Working, Work from Abroad, Sports & Social, Bike to Work, Travel Tax Saver
Paid Leaves: Annual Leave, Company Days, Friday Unplugged, Menstrual & Menopause Leave, Marriage & Civil Partnership Leave, Volunteer Days
Wellbeing: Subsidized Health Insurance, EAP, Flu Vaccines, Health Stations

Research shows that individuals from underrepresented backgrounds often hesitate to apply for roles unless they meet every single qualification, while others may apply when they meet only a portion of the criteria. If you believe you have the skills and potential to succeed in this role, even if you don't meet every listed requirement, we encourage you to apply. We'd love to hear from you and explore whether you could be a great fit.","hiringOrganization":{"@type":"Organization","name":"CarTrawler","sameAs":"https://corporate.cartrawler.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dublin","addressCountry":"Ireland","addressRegion":"Europe"}}}},{"@type":"ListItem","position":37,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (Fulfilment)","datePosted":"2025-09-22","description":"

Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to Know the Team

The Fulfilment Tech Family is a foundational part of Grab, enabling seamless coordination between our diverse marketplaces across Southeast Asia. We design real-time, distributed systems and machine learning solutions to process hundreds of millions of requests per day, driving efficient supply allocation, pricing, and order matching. Our mission:

Deliver best-in-class products for our driver-partners.
Maximise efficiency in fulfilling consumer demand – rain or shine.
Create sustainable, efficient marketplaces that balance experience and cost for all stakeholders.

We're looking for a Senior Machine Learning Engineer to join our Fulfilment team and take the lead in Fulfilment strategy optimization – bringing existing optimisation and automation of our pricing, dispatch and supply management policies to the next level.

Get to Know the Role

You'll optimize cross-system fulfilment strategies, and lead model development with user and driver behavioural prediction, optimisation and reinforcement learning (RL) techniques. Your primary objective will be to enhance marketplace operations by constructing interpretable, adaptable multi-agent RL systems or decision agents that can manage diverse objectives and disruptions.

You'll report to the Head of Data Science and work onsite at Grab's One North Singapore office.

The Critical Tasks You Will Perform

You'll design and implement cross-system strategies to improve operational efficiency in fulfilling user demands and boosting driving utilisation.
You'll build advanced DL and LLM models to capture the spatial-temporal patterns of dynamic marketplace conditions.
You'll develop advanced ML/DL models to predict user and driver behaviours, and use the behavioural insights to inform decision-making and platform interventions.
You'll build and deploy interpretable, adaptable optimisation models, RL systems or decision agents, that can handle multi-objectives and real-world disruptions.
You'll collaborate with machine learning engineers and backend engineers to integrate the ML/DL, optimization or RL models into real-time production systems.
You'll create technical documents outlining the methodologies and findings of your work. You'll also present solutions to non-technical stakeholders.

Qualifications

What Essential Skills You Will Need

You hold a Master degree in Computer Science, Operations Research, Applied Mathematics, or related field with at least 2 years of relevant experience.
You have professional experience or academic publications in Reinforcement Learning, Stochastic Control, Behavioural Modelling, Optimisation Under Uncertainty.
You have experience developing and deploying ML models that incorporate online learning, Markov Decision Processes, or simulation-based optimization.
You are fluent in Python and ML frameworks (e.g., PyTorch, TensorFlow).
You are familiar with distributed computing systems or scalable training platforms (e.g., Spark, Ray).
You can explore new ideas and learn new skills to accomplish tasks.

Additional Information

Life At Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

We have your back with Term Life Insurance and comprehensive Medical Insurance.
With GrabFlex, create a benefits package that suits your needs and aspirations.
Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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This role is for one of Weekday’s clients

Salary range: Rs 6000000 - Rs 7500000 (ie INR 60-75 LPA)

Min Experience: 10 years

Location: Bengaluru

JobType: full-time

Requirements

As a Lead Machine Learning Engineer, you will lead our efforts in leveraging large language and action models at scale to power our products. As a key member of the AI team, you will be working with other talented engineers to drive the development of novel agentic AI techniques, and integrate these new techniques into multiple product lines. This is an opportunity for someone who is passionate about productizing the latest research, has an interest in pushing the boundaries of what can be achieved with agents in a real-world setting, and isn't afraid to get their hands dirty in implementation details.

Responsibilities

Work closely with the backend team to design, develop, test, and maintain large language models, large action models and agents leveraging them at scale
Develop new techniques for training and using large language and action models
Develop novel agentic architectures around LLMs and LAMs to serve multiple products
Collaborate on the architecture and engineering of our AI infrastructure to ensure it is robust, scalable, maintainable and performant for multiple AI products
Drive and own development projects from concept through production. This includes research, prototyping, design, implementation, testing, documentation, training, and maintenance.
Work with other cross-functional teams such as product to help design the AI systems and models that power our products

Requirements

MS in ML/AI or a related field
8+ years of experience in machine learning or related field
Strong knowledge of large language models (LLMs) and transformer models.
Deep familiarity with a variety of deep learning technologies and architectures such as RNNs, attention mechanisms, long short-term memory (LSTM), and sequence-to-sequence models
Understanding of how to use a variety of deep learning technologies including PyTorch, Tensorflow and Keras
Excellent written and verbal communication skills.
Strong problem solving skills to resolve complex problems in creative ways
Ability to work independently as well as within a team

Preferred

Masters in ML/AI or a related field
Hands-on experience with all stages of LLM training and inference
Experience in reinforcement learning (RL)
Experience with large multi-modal models
Experience with agentic frameworks using LLMs (LangChain, LlamaIndex, MetaGPT , AutoGPT , etc)
Experience with neuro symbolic AI methods is a huge plus

","hiringOrganization":{"@type":"Organization","name":"Weekday","sameAs":"https://www.weekday.works"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru, Karnataka, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":39,"item":{"@type":"JobPosting","title":"Machine Learning Engineer I","datePosted":"2025-09-22","description":"

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line Of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$120,000 - $153,500 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Customer

Provide expertise on fundamental engineering practices for the broader AI/ML engineering team and inspire the adoption of ML engineering practice across the organization.
Interpret the meaning of new strategic directions and set objectives and measurements.
Implement monitoring and feedback systems to evaluate progress and identify ways of making continuous improvements.
Gather and analyze information or data on current and future trends of best engineering practices.
Seek information on issues impacting the progress of organizational, engineering and process issues.

Shareholder

Adhere to enterprise frameworks or methodologies that relate to activities for our business area.
Ensure respective programs/policies/practices are well managed, meets business needs, complies with internal and external requirements, and aligns with business priorities.
Consistently exercise discretion in managing correspondence, information and all matters of confidentiality; escalate issues where appropriate.
Ensure business operations are in compliance with applicable internal and external requirements (e.g., financial controls, segregation of duties, transaction approvals and physical control of assets)
Participate in cross-functional / enterprise / initiatives as a subject matter expert helping to identify risk / provide guidance for complex situations.
Conduct internal and external research projects; support the development/ delivery of presentations / communications to management or broader audience.
Conduct meaningful analysis at the functional or enterprise level using results to draw conclusions, make recommendations, assess the effectiveness of programs/ policies/ practices.
Monitor service, productivity and assess efficiency levels within own function and implement continuous process / performance improvements where opportunities exist.
Lead / facilitate and/or implement actions / remediation plans to address performance / risk /governance issues.
Actively manage relationships within and across various business lines, corporate and/or control functions and ensure alignment with enterprise and/or regulatory requirements.
Keep abreast of emerging issues, trends, and evolving regulatory requirements and assess potential impacts.
Maintain a culture of risk management and control, supported by effective processes in alignment with risk appetite

Employee / Team

Participate fully as a member of the team, support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensure timely communication of issues/ points of interest.
Provide thought leadership and/ or industry knowledge for own area of expertise in own area and participate in knowledge transfer within the team and business unit.
Keep current on emerging trends/ developments and grow knowledge of the business, related tools and techniques.
Participate in personal performance management and development activities, including cross training within own team.
Keep others informed and up to date about the status / progress of projects and / or all relevant or useful information related to day-to-day activities.
Contribute to team development of skills and capabilities through mentorship of others, by sharing knowledge and experiences and leveraging best practices.
Lead, motivate and develop relationships with internal and external business partners / stakeholders to develop productive working relationships.
Contribute to a fair, positive and equitable environment that supports a diverse workforce.
Act as a brand ambassador for your business area/function and the bank, both internally and/or externally

Breadth & Depth:

Work autonomously and is accountable for sound knowledge of AI/ML engineering fundamentals, and of various AI/ML engineering frameworks, tools, processes and procedures, as well as organization issues, best engineering practices and business/organization standards.
Sound knowledge of applications, systems, innovation, system design activities, best engineering practices, business/organization standard
Solves complex problems, takes new perspectives on existing solutions, independently performs tasks from end to end to deliver quality results and meet timelines. May work under guidance of more senior roles.
Generally, reports to a Senior Manager or above role.

Experience And / Or Education

Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science) Graduate's degree preferred with either progressive project work experience

Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we deliver legendary customer experiences to over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to the Bank, those we serve, and the economies we support. We are guided by our vision to Be the Better Bank and our purpose to enrich the lives of our customers, communities and colleagues.

TD is deeply committed to being a leader in customer experience, that is why we believe that all colleagues, no matter where they work, are customer facing. As we build our business and deliver on our strategy, we are innovating to enhance the customer experience and build capabilities to shape the future of banking. Whether you’ve got years of banking experience or are just starting your career in financial services, we can help you realize your potential. Through regular leadership and development conversations to mentorship and training programs, we’re here to support you towards your goals. As an organization, we keep growing – and so will you.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.

Colleague Development
If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities. Whether you have a passion for helping customers and want to expand your experience, or you want to coach and inspire your colleagues, there are many different career paths within our organization at TD – and we’re committed to helping you identify opportunities that support your goals.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.
Interview Process
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.

Accommodation
Your accessibility is important to us. Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.

We look forward to hearing from you!

Language Requirement (Quebec Only):

Sans Objet","hiringOrganization":{"@type":"Organization","name":"TD","sameAs":"https://www.td.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"661 University Avenue, Toronto, Ontario, Canada","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":40,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, Agentic AI – User Understanding","datePosted":"2025-09-22","description":"

About The Team

The Agentic AI team at Zillow is at the forefront of transforming the real estate industry by helping millions of people use AI technologies to find their next home. We aim to redefine the home shopping and transaction experience by providing an always-on assistant that integrates deep user insights and sophisticated reasoning. By embedding domain knowledge and specialized expertise in these assistants, we empower home buyers and real estate professionals to gain efficiency while maintaining Zillow’s competitive edge. This lean, customer-focused team comprises scientists and engineers working together to deliver a delightful customer experience. We strongly believe in accountability, collaboration, and transparency.

About The Role

Zillow is looking for a Machine Learning Engineer for the Agentic AI team to develop advanced agentic customer experiences. You will be hands-on in prototyping ideas, training large language models (LLMs), evaluating, and deploying them to Zillow’s highly scalable infrastructure platforms. You will develop models to gain deeper insights into user behavior and manage the decision-making processes of AI agents.

You Will Get To:

Build and maintain data pipelines for LLM (Large Language Model) training and evaluation, curate user-understanding signals (such as intents, preferences, and behavioral features), and ensure data quality, privacy, and proper dataset management.
Develop and manage labeling and feedback loops, including heuristics, annotation jobs, and prompt-based labeling, to create high-quality corpora, collaborating with Data Engineering and Applied Science partners to improve data coverage and reduce noise.
Design, prototype, and ship to production agentic AI solutions, including multi-agent systems using frameworks like LangGraph, and implement context-aware features in partnership with senior engineers.
Implement an evaluation framework to measure model quality on offline test sets (accuracy, bias, safety, user-intent coverage), and build dashboards to track improvements over time.
Lead and contribute to experimentation by implementing metrics, A/B tests, and monitoring, helping to harden prototypes for reliable rollouts.
Collaborate with senior engineers and cross-functional partners to select the right technologies, participate in code reviews, and share best practices (including mentoring interns or new hires as needed).
Summarize research findings and model evaluations into clear write-ups and demos for the team and cross-functional stakeholders.
Stay current on emerging agentic AI paradigms, implement paper-inspired proofs of concept, and contribute insights to the team roadmap.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.In California, Colorado, Connecticut, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Nevada, New Jersey, New York, Rhode Island, Vermont, Washington state, and Washington DC the standard base pay range for this role is $142,800.00 - $228,200.00 Annually. This base pay range is specific to California, Colorado, Connecticut, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Nevada, New Jersey, New York, Rhode Island, Vermont, Washington state, and Washington DC and may not be applicable to other locations.In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location.

Who You Are

You are a roll-up-the-sleeves and get-it-done engineer who can marry state-of-the-art technology with large-scale engineering. We are looking for someone who has:

A master’s degree or above, or equivalent experience in Computer Science, Electrical Engineering, or a related field, with an emphasis on building products using frontier multimodal LLMs (Large Language Models).
Expertise in agentic AI, pretraining, fine-tuning, and reinforcement learning of large language models.
3+ years of hands-on experience building large-scale, high-impact solutions, ideally with recent experience in agent-based systems, multi-agent collaboration, or similar paradigms.
Experience deploying and scaling AI services capable of handling hundreds of millions of daily interactions with high availability, low latency, and robust fault tolerance.
A track record of writing articles and publishing high-impact research in top AI conferences is a big plus.
Here at Zillow, we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.

Get To Know Us

Zillow is reimagining real estate to make home a reality for more and more people.

As the most-visited real estate website in the United States, Zillow® and its affiliates help movers find and win their home through digital solutions, first class partners, and easier buying, selling, financing and renting experiences. Millions of people visit Zillow Group sites every month to start their home search, and now they can rely on Zillow to help make it easier to move. The work we do helps people get home and no matter what job you're in, you will play a critical role in making home a reality for more and more people.

Our efforts to streamline the real estate transaction are supported by a deep-rooted culture of innovation, our passion to redefine the employee experience, a fundamental commitment to Equity and Belonging, and world-class benefits. These benefits include comprehensive medical, dental, vision, life, and disability coverages as well as parental leave, family benefits, retirement contributions, and paid time off. We’re also setting the standard for work experiences of the future, where our employees are supported in doing their best work and living a flexible, well-balanced life. But don’t just take our word for it. Read recent reviews on Glassdoor and recent recognition from multiple organizations, including: the 100 Best Companies to Work For, Glassdoor Employees’ Choice Award, Bloomberg Gender-Equality Index, Human Rights Campaign (HRC) Corporate Equity Index, and TIME 100 Most Influential Companies list.

Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.

Applicants who receive job offers from Zillow Group will be asked to sign a Proprietary Rights Agreement which includes confidentiality, intellectual property assignment, customer and employee non-solicitation, and non-competition provisions. If you are contacted for a role at Zillow Group and wish to review a copy of the Proprietary Rights Agreement prior to receiving an offer, you may request a copy from your Recruiter.

","hiringOrganization":{"@type":"Organization","name":"Zillow","sameAs":"https://www.zillow.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote-USA, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":41,"item":{"@type":"JobPosting","title":"Machine Learning Engineer III, MLOps","datePosted":"2025-09-21","description":"If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere.

Who we are:

ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with data solutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of the industry and we want you to join us on our journey. Our network of brands include ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services.

ACV Auctions in Chennai, India are looking for talented individuals to join our team. As we expand our platform, we're offering a wide range of exciting opportunities across various roles in corporate, operations, and product and technology. Our global product and technology organization spans product management, engineering, data science, machine learning, DevOps and program leadership. What unites us is a deep sense of customer centricity, calm persistence in solving hard problems, and a shared passion for innovation. If you're looking to grow, lead, and contribute to something larger than yourself, we'd love to have you on this journey. Let's build something extraordinary together. Join us in shaping the future of automotive!

At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs.

What you will do:
ACV’s Machine Learning (ML) team is looking to grow its MLOps team. Multiple ACV operations and product teams rely on the ML team’s solutions. Current deployments drive opportunities in the marketplace, in operations, and sales, to name a few. As ACV has experienced hyper growth over the past few years, the volume, variety, and velocity of these deployments has grown considerably. Thus, the training, deployment, and monitoring needs of the ML team has grown as we’ve gained traction. MLOps is a critical function to help ourselves continue to deliver value to our partners and our customers.
Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of their stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable.
The core responsibilities of this role are:
• Working with fellow machine learning engineers to build, automate, deploy, and monitor ML applications.
• Developing data pipelines that feed ML models.
• Deploy new ML models into production.
• Building REST APIs to serve ML models predictions.
• Monitoring performance of models in production.
Required Qualifications:
• Graduate education in a computationally intensive domain or equivalent work experience.
• 2-4 years of prior relevant work or lab experience in ML projects/research, and 1+ years as tech lead or major contributor on cross-team projects.
• Advanced proficiency with Python, SQL etc.
• Experience with cloud services (AWS / GCP) and kubernetes, docker, CI/CD.
Preferred Qualifications:
• Experience with MLOps-specific tooling like Vertex AI, Ray, Feast, Kubeflow, or ClearML, etc. are a plus.
• Experience with EDA, including data pipeline building and data visualization.
• Experience with building ML models.

Our Values
Trust & Transparency | People First | Positive Experiences | Calm Persistence | Never Settling

At ACV, we are committed to an inclusive culture in which every individual is welcomed and empowered to celebrate their true selves. We achieve this by fostering a work environment of acceptance and understanding that is free from discrimination. ACV is committed to being an equal opportunity employer regardless of sex, race, creed, color, religion, marital status, national origin, age, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires reasonable accommodation, please let us know.

Data Processing Consent

When you apply to a job on this site, the personal data contained in your application will be collected by ACV Auctions Inc. and/or one of its subsidiaries (\"ACV Auctions\"). By clicking \"apply\", you hereby provide your consent to ACV Auctions and/or its authorized agents to collect and process your personal data for purpose of your recruitment at ACV Auctions and processing your job application. ACV Auctions may use services provided by a third party service provider to help manage its recruitment and hiring process. For more information about how your personal data will be processed by ACV Auctions and any rights you may have, please review ACV Auctions' candidate privacy notice here. If you have any questions about our privacy practices, please contact datasubjectrights@acvauctions.com.","hiringOrganization":{"@type":"Organization","name":"ACV Auctions","sameAs":"https://www.acvauctions.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chennai, TN, 600096, IN","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":42,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-21","description":"

Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways.

You will be joining a team of talented developers that share a common interest in distributed backend systems, data, scalability, and continued development. You will get a chance to apply these, and other skills, to new and ongoing projects to make machine learning more approachable, data more available, and easier to discover and use by helping design how teams build out AI powered features at Weave.

Our teams are cross-functional agile teams composed of a product owner, backend and frontend devs and devops. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest.

Above all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture.

Purpose

The Machine Learning Team's mission is to enable product innovation by making it painless for developers to build ai powered applications that require access to large sets of data. Machine learning is challenging but we are striving to democratize access to the tools and technology that powers it so teams can build cutting edge features safely and responsibly without a PhD in Data Science. As a Machine Learning Engineer on the team you’ll be building models for new products with emerging technologies, at scale. We handle data for hundreds of millions of people daily.

This position will be available for fully remote in the US with an opportunity to work in an office, if located near the Lehi, UT Headquarters.
Reports to: Engineering Director

What You Will Own

Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.
Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning.
Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products.
Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning. Guide them through creating excellent customer experiences end to end.
Build scalable, resilient services to support data integration, event processing, and platform extensions.
Contribute to the continued evolution of product functionality that services large amounts of data and traffic.
Write code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.
Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.
Work in a cloud environment, considering the implementation of functionality through several distributed components and services.
Work with our stakeholders to translate product goals into actionable engineering plans.

What You Will Need to Accomplish the Job

High integrity, team-focused approach, and collaboration skills to build tight-knit relationships across Weave with various roles and stakeholders.
Responsive person with a strong bias for action.
5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).
Experience moving and storing TBs of data or 100M’s to 10B’s of records.
Experience building and deploying ML driven B2B multi-tenant applications in production environments.
Experience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
Experience with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine Tuning, multi-modal models, and others.
Experience with data labelling or annotation for audio or text use cases.
Understanding of distributed systems and building scalable, redundant, and observable services.
Expertise in designing and architecting systems for distributed data sets and services.
Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
Experience providing stable well designed libraries and SDKs for internal use.
Self driven and a thirst for learning in a quickly changing industry.
Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.
Strategic thinker with a strong technical aptitude and a passion for execution.

What Will Make Us Love You

A background with data analysis, visualization, and presentation.
3+ years of experience in data science, machine learning, or predictive analytics in addition to engineering experience.
Experience with natural language models, embeddings, and inference in production, at scale.
Experience with real-time audio models and voice use cases such as transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis.
Experience with emerging technologies such as Model Context Protocol (MCP).
Proficient understanding of containers, orchestrators, and usage patterns at scale including networking, storage, service meshes, and multi-cluster communication. Experience with Kubernetes or GKE and the Operator Pattern (GCP), specifically, a plus.
Experience with highly sensitive data such as PHI (HIPAA) and PII data.
Experience with automation and container based workflow engines.
Experience with GitOps, IaC, and configuration driven systems.
A preference for open source solutions.
A track record of clean abstractions and simple to use APIs.
Deep understanding of distributed data technologies such as streaming, data mesh, data lakes, warehouses, or distributed machine learning.
A desire to advance the state of the art with new and innovative technologies.
Enjoys working in a greenfield environment using rapid prototyping.
Enjoys working with open-ended, evolving problems, and domains.

Weave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know.

All official correspondence will occur through Weave branded email. We will never ask you to share bank account information, cash a check from us, or purchase software or equipment as part of your interview or hiring process.

","hiringOrganization":{"@type":"Organization","name":"Weave","sameAs":"https://www.getweave.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US Remote","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":43,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (5+ years) | Nepal","datePosted":"2025-09-21","description":"About Docsumo:Docsumo is your go-to Document AI solution for streamlining business operations. We turn complex documents like bank statements, policies, and financial statements into valuable, actionable data. Our cutting-edge technology helps businesses make smarter decisions faster. We are backed by marquee investors such as Sequoia, Barclays, Fifth Wall, Common Ocean, and Techstars.
At Docsumo, we're on a mission to revolutionize how businesses handle data. We empower companies to:Boost efficiency by 6-10 timesMake quick, accurate decisions from unstructured informationScale operations effortlessly through innovative technology\n

The Opportunity As Senior Machine Learning Engineer:

We are seeking senior professionals with over 4 years of experience in the field. This is a role for candidates with a proven track record in machine learning, deep learning, NLP, and computer vision.
If you have led and managed a team of ML scientists and engineers and have a strong foundation in deploying end-to-end ML solutions, this opportunity is for you.
This role offers the chance to rapidly advance into leadership positions, such as Lead ML Engineer, where you'll spearhead critical projects with creative autonomy.
You'll work closely with our CTO, Data Science, and Engineering teams, shaping the future of intelligent document processing for our expanding client base in the US.
This is a full-time role with flexible options, including hybrid work in Kathmandu or remote work from India.
Working hours are 10:00 am to 7:00 pm IST, with a 1-hour lunch break.
You will report directly to the Data Science Lead or the CTO, collaborating with a talented team to deliver innovative ML solutions that drive customer success.

Key Responsibilities

Collaborate with cross-functional teams of scientists and engineers to design, develop, and implement advanced machine learning systems that transform innovative ideas from conceptual stages into operational APIs.
Conduct cutting-edge research in machine learning, focusing on the application and fine-tuning of Large Language Models (LLMs) to develop robust, scalable solutions for intelligent document processing.
Lead a team of data scientists and machine learning engineers, providing mentorship and fostering a culture of collaboration and continuous learning to achieve high performance and innovative outcomes.
Plan, manage, and oversee the full lifecycle of ML projects, ensuring alignment with business goals and timely delivery of high-quality solutions. Develop and apply sophisticated machine learning algorithms to address complex business challenges, particularly those involving the processing and analysis of unstructured data.
Engage in Agile development processes including regular standups, sprint planning, and retrospectives to facilitate iterative progress and maintain high standards of output.
Ensure the documentation of machine learning methodologies, model development processes, and maintain rigorous testing standards to ensure reliability and efficiency of models in production.
Drive the integration and optimization of LLMs and other advanced models to enhance performance and operational efficiency, continuously seeking improvements.

Need To Have:

At least 5 years of industry experience in machine learning, deep learning, NLP, and computer vision, ideally within tech companies, product startups, or R&D environments.
1-2 years of experience leading teams of 4-5+ ML scientists and engineers, demonstrating effective leadership and project management skills. Proficiency in PyTorch and TensorFlow, with experience in training deep neural networks, implementing transfer learning, and optimizing models.
Strong skills in classification and regression techniques, with hands-on experience in Scikit-learn, Numpy, Pandas, and Scipy. Practical experience with Transformers, such as BERT and GPT, for tasks like text classification, entity recognition, and sentiment analysis.
Proficiency in Python and strong understanding of Object-Oriented Programming (OOP) principles.
Experience with version control using Git, cloud platforms like AWS and Google Cloud, and containerization technologies such as Docker and Kubernetes.
Ability to work effectively in a team, demonstrating motivation, resourcefulness, and a growth mindset.
Bachelor’s degree in Computer Science, Statistics, Machine Learning, Physics, Mathematics, or a related field.

Nice To Have:

Experience with Large Language Models, including techniques like PEFT, prompt engineering, few-shot learning, and RLHF.
Knowledge of computer vision applications like OCR, OpenCV, CNNs, and multimodal AI.
Experience with advanced data visualization libraries.
Familiarity with Agile development practices and sprint management.
A track record of innovative research contributions or publications in the machine learning domain.

","hiringOrganization":{"@type":"Organization","name":"Docsumo","sameAs":"https://www.docsumo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Kathmandu, Nepal","addressCountry":"Nepal","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":44,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Senior Consultant","datePosted":"2025-09-21","description":"

Senior Machine Learning Engineer

The Software Engineering team delivers next-generation application enhancements and new products for a changing world. Working at the cutting edge, we design and develop software for platforms, peripherals, applications and diagnostics — all with the most advanced technologies, tools, software engineering methodologies and the collaboration of internal and external partners.

Join us to do the best work of your career and make a profound social impact as a Senior Machine Learning Engineer on our Software Engineering Team in our Client Solutions Group.

What You’Ll Achieve:

As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that power intelligent tools and features across our products. This role requires strong technical expertise, a collaborative mindset, and a passion for solving real-world problems using data.

You Will:

Design and implement AI algorithms and models for real-world applications (e.g., NLP, computer vision, recommendation systems).
Collaborate with cross-functional teams to integrate AI solutions into products and services.
Optimize and scale machine learning models for performance and efficiency.
Maintain and improve existing AI systems through continuous learning and feedback loops.
Conduct research and stay up-to-date with the latest advancements in AI and machine learning.
Write clean, maintainable, and well-documented code.
Participate in code reviews, testing, and deployment processes.

Essential Requirements

15-20 years of combined experience in the architecture, design and development of BIOS Firmware , Artificial Intelligence, Machine Learning, or related field with Bachelor’s or Master’s degree.
Strong programming skills in Python (preferred), C++, or Java.
Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
Solid understanding of data structures, algorithms, and software engineering principles.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes).
Experience and deep learning, reinforcement learning, or generative models.
Knowledge of MLOps practices and tools.

Desirable Requirements

Prior experience deploying AI models in production environments preferred.
Contributions to open-source AI projects or published research preferred.

Who We Are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 15-Oct-25

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.

","hiringOrganization":{"@type":"Organization","name":"Dell Technologies","sameAs":"https://www.delltechnologies.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":45,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-20","description":"

At Prodigal, we’re reshaping the future of consumer finance. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades.

Today, we stand at the forefront of a seismic shift in the industry, pioneering the concept of consumer finance intelligence. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine, we’re creating the next-generation agentic workforce for consumer finance—one that empowers companies to achieve unprecedented levels of operational excellence.

With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build generative AI solutions that will revolutionize the future of consumer finance.

At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.

We are looking for a passionate and seasoned Senior Machine Learning (ML) Engineer to spearhead the design, development, and deployment of cutting-edge Machine Learning and Generative AI solutions towards Prodigal’s vision of building the Intelligence Layer for Consumer Finance.

Responsibilities:

ML Algorithm Development: Design and implement advanced ML algorithms leveraging traditional Machine Learning techniques and the modern NLP stack, including Large Language Models (LLMs)
Data Engineering & Software Development: Architect and implement data pipelines for ML model training. Lead scalable software systems development to deploy ML models into production systems, ensuring high performance and reliability.
Research & Innovation: Stay updated on ML research and the ever-changing Gen AI landscape, identifying opportunities for innovation.
Collaboration & Leadership: Effectively collaborate with cross-functional teams to deliver high-quality solutions on time. Guide team members in contributing to ML design discussions for new projects.

Requirements:

Extensive experience (5-8 years) in software development, with a focus on machine learning and data science in a tech company.
Proven track record of delivering high-quality ML products in a fast-paced, agile environment.
Deep understanding of machine learning algorithms with hands-on experience in developing and deploying machine learning models at scale.
Strong coding skills in Python. Familiarity with machine learning libraries such as PyTorch and sci-kit-learn. Experience with data manipulation and analysis tools like Pandas and Spark.
Strong communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and mentor junior engineers.

Preferred Qualifications:

Experience training and using Large Language Models (BERT, LLAMA, GPT etc) with a passion for applying Generative AI solutions in production environments.
Experience with cloud services (AWS) and building scalable, distributed systems.

Mode Of Work - In-Office

\n\n

Job Benefits

World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
Health insurance - Health always comes first. The health of your family is as important to us, as it is to you. We offer insurance coverage for both you and your family.
Flexible schedule - We're not a \"clock in, clock out\" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation allowance here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions and challenge each other to do those extra push ups or chug that 4th drink (of course that’s Nimbu Pani)

\n\n

Meet Sangram - (Cofounder and CTO) and hear his vision for Prodigal below (01:38)

From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.

To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
Our website - https://www.prodigaltech.com/

At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.

About The Role

We're looking for a curious and resilient Machine Learning Engineer who thrives in a culture of experimentation and rapid iteration. Our ideal candidate doesn't just apply AI concepts – they're excited to push boundaries, challenge assumptions, and learn from both successes and failures. If you believe that the only true failure is not experimenting quickly, we want you on our team.

Key Responsibilities

Embrace a \"fail fast, learn faster\" mentality, aiming for a 20-30% success rate in your ideas and experiments. Continuously optimize our experimentation process, making it faster, more efficient, and more insightful
Apply AI concepts to solve business problems, with a focus on rapid prototyping and iterative improvement
Leverage SQL and data manipulation tools to work with complex datasets, exploring unconventional approaches
Apply statistical methods, machine learning algorithms, and data visualization techniques to perform exploratory data analysis, embracing unexpected insights
Build and interpret models using tools like PySpark and ML-Flow, constantly testing new approaches and parameters
Write clean, well-documented code that facilitates collaboration and hence faster iteration
Continuously evaluate and enhance existing models, viewing each iteration as an opportunity to learn and improve

Technical Skills

Proficiency in rapidly prototyping and testing ideas using large, complex datasets and SQL
Expertise in implementing and iterating on machine learning models and algorithms, with a focus on quick experimentation cycles
Strong programming skills in Python and/or SQL, with an emphasis on writing code that facilitates easy modification and testing
Experience in leveraging data visualization techniques to quickly interpret and communicate experimental results
Ability to swiftly deploy and iterate on AI solutions in cloud environments

Soft Skills

Passionate about experimentation and embracing failure, viewing setbacks as valuable learning opportunities
Excellent written and verbal communication skills, able to articulate the value of experimentation and rapid iteration to stakeholders
Thrives in ambiguity and uncertainty, comfortable with the idea that most experiments will not succeed; also designing good experiments is a crucial part of the R&D process
Skilled at analyzing problems from multiple angles and generating a high volume of potential solutions

Preferred Qualifications

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Tier 1 colleges are preferred)
Minimum of 3 years of hands-on experience in data analysis, modeling, and AI solutions development

If you're passionate about leveraging data to drive business decisions and have a track record of delivering impactful AI solutions, we want to hear from you!

Mode of Work - On-Site

Job Benefits

GenAI experience – Work directly in the innovative field of GenAI, shaping groundbreaking projects that redefine consumer finance intelligence.
World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
Health insurance - Health always comes first. The health of your family is as important to us, as it is to you. We offer insurance coverage for both you and your family.
Flexible schedule - We're not a \"clock in, clock out\" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions and challenge each other to do those extra push ups or chug that 4th drink (of course that’s Nimbu Pani).

To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
Our website - https://www.prodigaltech.com/

\n\n\n","hiringOrganization":{"@type":"Organization","name":"Prodigal","sameAs":"https://www.prodigaltech.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mumbai","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":47,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - Global E-commerce Recommendation/Search","datePosted":"2025-09-20","description":"The Data-E-commerce team oversees algorithmic and corresponding engineering work in the e-commerce business. Our responsibilities encompass not only utilizing recommendation and search algorithms to help users discover appealing products but also implementing risk control and content safety algorithms to identify malicious sellers/influencers and violations in products/videos/live streams, ensuring a secure shopping experience. Furthermore, we are involved in constructing intelligent customer service technology and large-scale product knowledge graphs, aiming to enhance efficiency across various transaction processes. Through operations optimization and intelligent supply chain algorithms, we work to improve logistics efficiency.
\n
\nResponsibilities:
\n• Work in a team to conduct cutting-edge research in machine learning algorithms, such as retrieval and recommendation algorithms.
\n• Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.
\n• Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
\n• Apply machine learning algorithms to improve the different business scenarios, such as search ranking, natural language and video understanding, and trust and safety.","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose, California, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":48,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer","datePosted":"2025-09-19","description":"

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

#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":49,"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":50,"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.

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