Asks for

The ad says“Experience deploying, monitoring, and troubleshooting AI & ML models in a public cloud (we use AWS)”
The ad says“Contribute enhancements to the CarGurus ML platform, leveraging technologies such as AWS SageMaker, GitHub Actions, and Docker”
The ad says“Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization”
The ad says“Contribute enhancements to the CarGurus ML platform, leveraging technologies such as AWS SageMaker, GitHub Actions, and Docker”
The ad says“Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization”
The ad says“Contribute enhancements to the CarGurus ML platform, leveraging technologies such as AWS SageMaker, GitHub Actions, and Docker”
The ad says“A working understanding of the machine learning lifecycle, including model training, evaluation, deployment, and monitoring”
The ad says“Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)”
The ad says“Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization”
The ad says“Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)”
The ad says“4+ years experience writing and debugging Python code”
The ad says“Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)”
The ad says“Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)”
The ad says“Knowledge of SQL and familiarity with cloud data warehouses (we use Snowflake)”
The ad says“Knowledge of SQL and familiarity with cloud data warehouses (we use Snowflake)”
The ad says“Familiarity with software engineering tools and standard methodologies, e.g. git, unit testing, object-oriented design, containerization”
The ad says“Familiarity with the Python ML ecosystem (e.g. scikit-learn, XGBoost, PyTorch, numpy, pandas)”

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!

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

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

What you’ll bring

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

The displayed range represents the expected annual base salary / On-Target Earnings (OTE) for this position. On-Target Earnings (OTE) is inclusive of base salary and on-target commission earnings, which applies exclusively to sales roles.

Individual pay within this range is determined by work location and other factors such as job-related skills, experience, and relevant education or training.

This annual base salary forms part of a comprehensive Total Rewards Package. In addition to benefits, this role may qualify for discretionary bonuses/incentives and Restricted Stock Units (RSUs).

Position Pay Range

$144,000—$181,000 USD

Working at CarGurus

We reward our Gurus’ curiosity and passion with best-in-class benefits and compensation, including equity for all employees, both when they start and as they continue to grow with us. Our career development and corporate giving programs, as well as our employee resource groups (ERGs) and communities, help people build connections while making an impact in personally meaningful ways. A flexible hybrid model and robust time off policies encourage work-life balance and individual well-being. Thoughtful perks like daily free lunch, a new car discount, meditation and fitness apps, commuting cost coverage, and more help our people create space for what matters most in their personal and professional lives.

CarGurus may require in-person interviews as part of our hiring process, particularly for positions based in our Boston and Dublin offices. Candidates selected for an in-person interview will be notified in advance. Please be aware that travel expenses are the responsibility of the candidate.

We welcome all

CarGurus strives to be a place to which people can bring the ultimate expression of themselves and their potential—starting with our hiring process. We do not discriminate based on race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation. We foster an inclusive environment that values people for their skills, experiences, and unique perspectives. That’s why we hope you’ll apply even if you don’t check every box listed in the job description. We also encourage you to tell your recruiter if you require accommodations to participate in our hiring process due to a disability so we can provide the appropriate support. We want to know what only you can bring to CarGurus. #LI-Hybrid