About the Company
Turing is an AGI infrastructure company that works with leading AI research labs to accelerate model development. Its work includes providing high-quality training data, model evaluations, and engineering talent to support the development of advanced AI systems.
About the Role
Turing is seeking an engineer with strong technical judgment and hands-on experience working with preference data and evaluation rubrics. This role combines data quality review, evaluation design, and engineering work to support AI training and assessment workflows.
You'll help define what high-quality examples look like, develop and refine evaluation criteria, and identify subtle issues in data that could affect model performance. The position also involves building and maintaining the pipelines and infrastructure needed to generate, collect, and evaluate data. You'll work closely with researchers and engineers to turn qualitative judgments into consistent, scalable processes.
The ideal candidate communicates clearly, works comfortably in fast-moving and ambiguous environments, and can turn complex technical findings into concise, actionable recommendations.
Key Responsibilities
Design, refine, and iterate on rubrics and evaluation criteria for preference data.
Review and label data while maintaining high quality standards and identifying subtle errors or inconsistencies.
Build and maintain pipelines and infrastructure supporting data generation, collection, and evaluation workflows.
Summarize findings from data-related work in clear write-ups, progress updates, and recommendations.
Collaborate with researchers and engineers to translate qualitative judgments into scalable evaluation processes.
Required Qualifications
Proficiency in Python, particularly for building and maintaining pipelines and infrastructure, or TypeScript.
Hands-on experience with preference data collection, rubric creation, or both.
Strong written and verbal communication skills, including the ability to explain technical work in concise, actionable terms.
Strong quality judgment and the ability to explain why a particular example or result is good, rather than simply identifying it as good or bad.
Preferred Technical Experience
Experience contributing to or navigating large TypeScript codebases, such as VSCode.
Engagement Details
Compensation: Market rate. Candidates should provide a specific rate expectation rather than a range.
Availability: 40 hours per week is preferred. A minimum of six hours of overlap with Pacific Time is required. Candidates unable to commit to 40 hours should specify their available hours and overlap window.
Duration: Three months, with an expected start as soon as possible.
Benefits: This independent contractor engagement does not include medical or paid leave benefits.
Freelance Opportunity The engagement offers fully remote work and the opportunity to contribute to advanced AI projects with leading large language model (LLM) companies.
Evaluation Process The selection process consists of one interview lasting approximately 30 minutes, covering technical skills and cultural fit.