Python 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 is for an engineer with strong quality judgment and hands-on experience with preference data and rubric creation. The engineer should communicate clearly, synthesize complex technical work into concise and actionable updates, and be comfortable working in ambiguous, fast-moving environments with an emphasis on shipping. The role involves designing and refining evaluation criteria, reviewing data for quality, building and maintaining supporting pipelines and infrastructure, synthesizing findings, and collaborating with researchers and engineers to make qualitative judgment scalable. This is a fully remote, independent-contractor engagement lasting three months, with an expected start as soon as possible. Compensation is at market rate, and applicants are asked to provide a specific rate expectation. Availability of 40 hours per week is preferred, with at least six hours of overlap with Pacific Time; applicants who cannot commit to 40 hours should provide their availability and overlap window. The selection process consists of one approximately 30-minute technical and cultural interview. The engagement does not include medical or paid leave benefits.
Requirements
- Proficiency in Python, particularly for building and maintaining pipelines and infrastructure, or proficiency in TypeScript.
- Hands-on experience with preference data collection and/or rubric creation.
- Strong written and verbal communication skills, including the ability to distill technical work into clear, actionable summaries.
- Strong quality judgment and the ability to articulate why something is good, not merely identify that it is.
Nice To Haves
- Experience contributing to or navigating large codebases such as VSCode.
- Availability for 40 hours per week is preferred, with a minimum six-hour overlap with Pacific Time.
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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