Senior ML Platform Engineer (Hybrid)

CarGurus; Boston (MA); Hybrid; USD 144,000 - 181,000; Full time

Job summary

CarGurus seeks a Machine Learning Operations Engineer to enhance and maintain its cloud-hosted ML platform. You will partner with data scientists to deploy models to production, build APIs and data pipelines, and contribute to systems for Recommendations, Search Ranking, and more.

You will write production-grade training jobs and inference APIs, integrate multi-modal AI, and design scalable workflows across the ML lifecycle, including deployment, monitoring, and optimization.

Qualifications

• 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

Skills

Python

Git

Unit testing

OO design

Docker

ML lifecycle

Python ML ecosystem

AWS

SQL

Snowflake

Tools

AWS SageMaker

GitHub Actions

Docker

Job description

CarGurus seeks a Machine Learning Operations Engineer to enhance and maintain its cloud-hosted ML platform. You will partner with data scientists to deploy models to production, build APIs and data pipelines, and contribute to systems for Recommendations, Search Ranking, and more.

You will write production-grade training jobs and inference APIs, integrate multi-modal AI, and design scalable workflows across the ML lifecycle, including deployment, monitoring, and optimization.