<div class="content-intro">Who we are At CarGurus (NASDAQ: CARG), our mission is to give people the power to reach their destination. We started as a small team of developers determined to bring trust and transparency to car shopping. Since then, our history of innovation and go-to-market acceleration has driven industry-leading growth. In fact, we’re the largest and fastest-growing automotive marketplace, and we’ve been profitable for over 15 years. What we do The market is evolving, and we are too, moving the entire automotive journey online and guiding our customers through every step. That includes everything from the sale of an old car to the financing, purchase, and delivery of a new one. Today, tens of millions of consumers visit CarGurus.com each month, and ~30,000 dealerships use our products. But they're not the only ones who love CarGurus—our employees do, too. We have a people-first culture that fosters kindness, collaboration, and innovation, and empowers our Gurus with tools to fuel their career growth. Disrupting a trillion-dollar industry requires fresh and diverse perspectives. Come join us for the ride!</div>Role overview 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. What you’ll do <ul> <li>Write production-quality training jobs and inference APIs for our Python ML models, deploying them to robust scalable services</li> <li>Contribute enhancements to the CarGurus ML platform, leveraging technologies such as AWS SageMaker, GitHub Actions, and Docker</li> <li>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</li> <li>Develop in-house tools and libraries to standardize and accelerate the AI and ML development process</li> <li>Build and integrate multi-modal AI capabilities into production ML systems</li> <li>Design and build agentic AI systems and harness engineering to enable autonomous, reliable software development workflows</li> <li>Own and maintain aspects of the Data Science team’s engineering infrastructure </li> <li>Promote and foster an inclusive, transparent, and collaborative culture</li> </ul> What you’ll bring <ul> <li>4+ years experience writing and debugging Python code</li> <li>Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization </li> <li>A working understanding of the machine learning lifecycle, including model training, evaluation, deployment, and monitoring</li> <li>Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas) </li> <li>Experience deploying, monitoring, and troubleshooting AI & ML models in a public cloud (we use AWS) </li> <li>Exposure to a variety of AI & ML systems in production, including regression and classification on tabular data, image models, language models, and agentic systems</li> <li>Knowledge of SQL and

Senior Machine Learning Operations Engineer

Job Description