Sourcegraph
The Staff ML and Agent Engineer on the Code Understanding team at Sourcegraph leads the development of AI-powered code search and analysis tools, setting technical direction for models, evaluations, and agentic systems. This role involves designing reliable, multi-step agent loops, optimizing model selection and training, and establishing robust evaluation frameworks to improve product quality and efficiency. The engineer will mentor teammates, drive the team's roadmap, and ensure the scalable deployment of AI solutions across enterprise codebases.
Headquarters
San Francisco, California, United States
Company Size
51-200 employees
Founded
2013
Sourcegraph is an enterprise code-intelligence platform that gives developers and AI agents instant context and control across every repository, branch, and language. It provides scalable universal code search and cross-repo code navigation so teams can find, understand, and change code quickly even in large, complex codebases where other tools break. Sourcegraph integrates with code hosts, CI/CD, and IDEs to speed code review, debugging, and automated developer workflows. Organizations choose it for its scalability, language-agnostic coverage, and ability to boost developer productivity and governance.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
View leadership team, funding history,
and employee contacts for Sourcegraph.
23% below the average for this role
Sourcegraph automates ‘soul-crushing’ tasks with AI coding agents
Jan 30, 2025