Python Engineer

Turing

9h•Remote

About The Position

Turing is a leading AGI infrastructure company that works with frontier AI labs to accelerate model development through high-quality 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 ideal candidate communicates clearly, can synthesize complex technical work into concise, structured, actionable information, and is comfortable in ambiguous, fast-moving environments with a bias toward shipping. The engineer will design and refine rubrics and evaluation criteria for preference data, review and label data to a high quality standard, build and maintain supporting pipelines and infrastructure, synthesize findings into clear team updates and recommendations, and collaborate with researchers and engineers to scale qualitative judgment into repeatable processes. This is a fully remote, independent contractor engagement expected to last three months, with a start as soon as possible. The preferred commitment is 40 hours per week, with at least six hours of overlap with Pacific Time. Compensation is market rate; applicants are asked to provide a specific rate expectation. The evaluation process is approximately 30 minutes and consists of one technical and cultural discussion.

Requirements

Proficiency in Python, particularly 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 explain why something is good, not just 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; candidates with fewer hours may share their availability and overlap window.
A minimum six-hour overlap with Pacific Time is requested.

Responsibilities

Design, refine, and iterate on rubrics and evaluation criteria for preference data.
Review and label data while identifying subtle quality issues.
Build and maintain pipelines and infrastructure for 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.