Senior Machine Learning Operations Engineer

CarGurus • Boston, MA

22h • $144,000 - $181,000 • Hybrid

About The Position

As a core member of the Machine Learning Platform team, the Machine Learning Operations Engineer will be responsible for enhancing and maintaining CarGurus’ cloud-hosted ML platform. You will partner closely with data scientists to deploy machine learning models to production and to build and maintain the APIs and data pipelines that integrate predictive intelligence into CarGurus’ products. You will have the opportunity to contribute to systems supplying Recommendations, Search Ranking, Computer Vision, Instant Market Value, and more.

Requirements

• 4+ years experience writing and debugging Python code
• Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization
• A working understanding of the machine learning lifecycle, including model training, evaluation, deployment, and monitoring
• Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)
• Experience deploying, monitoring, and troubleshooting AI & ML models in a public cloud (we use AWS)
• Exposure to a variety of AI & ML systems in production, including regression and classification on tabular data, image models, language models, and agentic systems
• Knowledge of SQL and familiarity with cloud data warehouses (we use Snowflake)
• A systems thinking mindset, able to reason about how components interact end-to-end across the ML lifecycle and platform, and also optimizing any single piece

Responsibilities

• Write production-quality training jobs and inference APIs for our Python ML models, deploying them to robust scalable services
• Contribute enhancements to the CarGurus ML platform, leveraging technologies such as AWS SageMaker, GitHub Actions, and Docker
• Participate in systems design conversations with our data scientists and engineering partners, using your engineering expertise and experience to help them design scalable and robust systems
• Develop in-house tools and libraries to standardize and accelerate the AI and ML development process
• Build and integrate multi-modal AI capabilities into production ML systems
• Design and build agentic AI systems and harness engineering to enable autonomous, reliable software development workflows
• Own and maintain aspects of the Data Science team’s engineering infrastructure
• Promote and foster an inclusive, transparent, and collaborative culture

Benefits

• equity for all employees, both when they start and as they continue to grow with us
• career development and corporate giving programs
• employee resource groups (ERGs) and communities
• flexible hybrid model
• robust time off policies
• daily free lunch
• new car discount
• meditation and fitness apps
• commuting cost coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed