About the Role

We are seeking a talented Machine Learning Engineer to join our growing team. In this role, you will design, develop, and deploy machine learning models and systems that solve complex business problems and deliver measurable impact. You'll work at the intersection of data science and software engineering, transforming innovative ML solutions from prototype to production-ready systems that serve millions of users.

Key Responsibilities

Design, build, and deploy scalable machine learning models and pipelines for production environments
Collaborate with data scientists to translate ML prototypes into robust, production-grade systems
Develop and maintain ML infrastructure, including training pipelines, model serving systems, and monitoring tools
Optimize model performance, latency, and resource utilization for large-scale deployments
Implement MLOps best practices including version control, automated testing, and continuous integration/deployment
Work with cross-functional teams including product managers, software engineers, and data scientists to understand requirements and deliver solutions
Monitor model performance in production and implement retraining strategies to maintain accuracy
Research and evaluate new ML techniques, frameworks, and tools to improve existing systems
Document technical designs, model architectures, and deployment procedures
Contribute to code reviews and mentor junior team members on ML engineering best practices

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or related field
3+ years of experience in machine learning engineering or related role
Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
Proven experience deploying and maintaining ML models in production environments
Solid understanding of machine learning algorithms, deep learning architectures, and statistical methods
Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes)
Proficiency in data processing frameworks such as Spark, Pandas, or Dask
Strong software engineering fundamentals including data structures, algorithms, and design patterns
Experience with version control systems (Git) and CI/CD pipelines
Excellent problem-solving skills and ability to work independently

Preferred Qualifications

Advanced degree (Ph.D. or Master's) in Machine Learning, AI, or related field
Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker
Knowledge of distributed computing and large-scale data processing
Experience with real-time model serving and low-latency inference systems
Familiarity with feature stores, model registries, and experiment tracking platforms
Background in specific ML domains such as NLP, computer vision, recommendation systems, or time series forecasting
Experience with A/B testing and experimental design
Contributions to open-source ML projects or published research papers
Strong communication skills and experience presenting technical concepts to non-technical stakeholders

What We Offer

Competitive salary and equity compensation package
Comprehensive health, dental, and vision insurance
Flexible work arrangements with remote work options
Professional development budget for courses, conferences, and certifications
Access to cutting-edge ML infrastructure and computational resources
Collaborative team environment with opportunities to work on challenging problems
Generous paid time off and company holidays
401(k) retirement plan with company matching
Wellness programs and mental health support
Regular team events and learning sessions

Equal Opportunity Statement

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to creating an inclusive environment for all employees.

ML Engineer