Remote Software Engineer - Python/Typescript
About The Position
Turing is seeking experienced, hands-on software engineers to evaluate and improve AI coding models. The role focuses on working with coding agents across real-world software repositories and assessing the quality of their work, rather than primarily building production applications. The engineer reviews generated code and agent behavior, judges technical correctness and quality, identifies failure modes, and creates evaluation signals and feedback to improve model performance. The position also involves developing evaluation and preference data, and building and maintaining pipelines and infrastructure for data generation, collection, and evaluation workflows. The engineer will collaborate with researchers and engineers to turn qualitative technical judgment into scalable processes and communicate actionable findings through clear write-ups, updates, and recommendations. This is an independent contractor engagement for approximately three months. The role is remote and open to candidates in North America, LATAM, or India. Forty hours per week are preferred, with at least six hours of Pacific Time overlap. The start is as soon as possible. The hiring process includes an AI interview, a practical code and AI evaluation exercise, and a hiring manager interview.
Requirements
- At least 5 years of hands-on software engineering experience.
- Strong proficiency in Python, TypeScript/JavaScript, Go, or another major production language.
- Experience working in substantial real-world codebases.
- Strong code-review skills and technical judgment.
- Ability to clearly explain why an implementation is correct, incorrect, or could be improved.
- Strong written communication.
- Experience using modern LLMs or AI coding tools.
- Availability of 40 hours per week is preferred, with at least 6 hours of Pacific Time overlap.
- Provide a specific hourly rate expectation.
Nice To Haves
- Experience with LLM evaluation, coding agents, RLHF, preference data, rubric design, or post-training.
Responsibilities
- Evaluate AI-generated code and solutions across real-world software repositories.
- Review coding-agent behavior, tool usage, and code changes for correctness and quality.
- Identify technical errors, weak approaches, and recurring model failure modes.
- Compare model outputs and explain why one solution is better than another.
- Create and refine rubrics and evaluation criteria for coding tasks.
- Produce evaluation and preference data used to improve coding models.
- Build and maintain pipelines and infrastructure supporting data generation, collection, and evaluation workflows.
- Synthesize findings from data work into clear write-ups, updates, and recommendations.
- Collaborate with researchers and engineers to translate qualitative judgment into scalable processes.
- Share clear, actionable findings with AI researchers and engineers.
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What This Job Offers
Career Level
Senior
Education Level
No Education Listed
