Python/Typescript Engineer
About The Position
Turing is an AGI infrastructure company that works with frontier AI labs to accelerate model development through training data, evaluations, and engineering talent. The role seeks an engineer with strong quality judgment and hands-on experience with preference data and rubric creation. The engineer should communicate clearly, synthesize technical work into concise and actionable outputs, and be comfortable working in ambiguous, fast-moving environments with a bias toward shipping. The work includes designing and refining rubrics and evaluation criteria for preference data; reviewing and labeling data to a high quality bar; building and maintaining infrastructure and pipelines for data generation, collection, and evaluation; summarizing findings for the team; and collaborating with researchers and engineers to scale qualitative judgment into processes. This is a fully remote, independent-contractor engagement for three months, with an expected start as soon as possible. Compensation is market rate; applicants are asked to provide a specific rate expectation. Forty hours per week is preferred, with at least six hours of overlap with Pacific Time. The evaluation process is one approximately 30-minute interview covering technical and cultural topics. The engagement does not include medical or paid-leave benefits.
Requirements
- Proficiency in Python, especially for building and maintaining pipelines and infrastructure, or in TypeScript.
- Hands-on experience with preference data collection and/or rubric creation.
- Strong written and verbal communication, including the ability to distill technical work into clear, actionable summaries.
- High-taste judgment and the ability to explain why something is good, not merely identify that it is.
Nice To Haves
- Experience contributing to or navigating large codebases such as VSCode.
Responsibilities
- Design, refine, and iterate on rubrics and evaluation criteria for preference data.
- Review and label data to a high quality standard, identifying subtle issues.
- Build and maintain pipelines and infrastructure supporting data generation, collection, and evaluation workflows.
- Synthesize findings from data work into clear write-ups, updates, or recommendations for the team.
- Collaborate with researchers and engineers to translate qualitative judgment into scalable processes.
Benefits
- Fully remote work environment.
- Opportunity to work on cutting-edge AI projects with leading LLM companies.
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