What the work is
Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.
Overview
Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented open-source maintainers and core contributors with deep, hands-on ownership of a mature, widely used open-source codebase to bring real-world engineering and code review judgment and elevate the quality of our AI training data. This is a full-time commitment of 40 hours per week.
Key Responsibilities
- Guide research and engineering teams to close knowledge gaps and improve AI model performance in software engineering, code review, and open-source maintenance topics.
- Design challenging, realistic engineering tasks grounded in the open-source codebase the expert knows best, such as the features, refactors and bug fixes a maintainer would assign, and write accurate, well-structured reference solutions.
- Evaluate AI-written code, tests and grading rubrics against the repository's architecture, conventions and quality bar, and provide clear, written technical feedback.
- Build, run and test the project locally, including with Docker, to confirm that tasks, solutions and tests behave as intended.
- Write precise rationales that explain what a strong solution looks like and where AI-generated changes fall short.
- Collaborate with other subject matter experts to ensure consistency and accuracy in training data.
Who gets hired
- Maintainer (named in MAINTAINERS or CODEOWNERS, or 10+ PR reviews in the last 12 months) or core contributor (3+ substantive merged PRs in the last 12 months) of a widely used open-source project.
- The repository is 2+ years old, has real users and an active code review culture, and is primarily human-written.
- Years of sustained open-source contributions, with a public history that can be verified against the candidate's own GitHub account.
- Senior-level code review judgment, including the ability to critically assess AI-written code, tests and edge cases.
- Hands-on ability to build and run the project and its test suite locally, including with Docker.
- Authorized to work in the United States on a W-2 basis.
- Able to complete any necessary background checks and confidentiality agreements before starting, and to work on a company-provided device to protect the security of information.
- Writes all rationales and feedback personally, in their own words.
- Strong written communication skills and the ability to explain complex technical decisions clearly.
The platform posted this on 2 Nov 2026.