AI Platform Engineer — Deploy & Scale ML in Production (Hybrid)

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

Benefits offered by this job

Hybrid work model

Daily lunch offered

New car discount

Commuting cost coverage

Job summary

CarGurus LLC is seeking an ML Operations Engineer to enhance and maintain a cloud-hosted ML platform. You will collaborate with data scientists to deploy models to production and build data pipelines that power features such as recommendations, search ranking, and computer vision.

You will write training jobs and APIs, participate in system design, and develop tools to standardize AI development workflows across teams. Hybrid work is available in our Boston-area offices.

Qualifications

• 4+ years of experience writing and debugging Python code.
• Familiarity with software engineering tools and standard methodologies (Git, unit testing, OO design, containerization).
• Understanding of the ML lifecycle: training, evaluation, deployment, monitoring.

Responsibilities

• Write production-quality training jobs and inference APIs for Python ML models; deploy to scalable services.
• Enhance CarGurus ML platform using AWS SageMaker, GitHub Actions, and Docker.
• Collaborate with data scientists to design robust, scalable ML systems.
• Develop in-house tools to accelerate AI/ML development.
• Build and integrate multi-modal AI capabilities into production ML systems.
• Design and build agentic AI systems to enable autonomous, reliable software workflows.
• Own and maintain aspects of the Data Science engineering infrastructure.
• Promote an inclusive, transparent, collaborative culture.

Skills

Python

ML lifecycle

AWS SageMaker

PyTorch

SQL

Snowflake

AI/ML systems

Multi-modal AI

Tools

Git

Unit testing

OO design

Containerization

Job description

CarGurus LLC is seeking an ML Operations Engineer to enhance and maintain a cloud-hosted ML platform. You will collaborate with data scientists to deploy models to production and build data pipelines that power features such as recommendations, search ranking, and computer vision.

You will write training jobs and APIs, participate in system design, and develop tools to standardize AI development workflows across teams. Hybrid work is available in our Boston-area offices.