Remote Software Engineer - Python/Typescript
About The Position
Turing is seeking experienced, hands-on software engineers to evaluate and improve AI coding models. The work focuses on using coding agents across real-world software repositories and assessing their work rather than primarily building production applications. Engineers review generated code and agent behavior, determine technical correctness, identify failure modes, and create evaluation signals and feedback to improve model performance. The role involves evaluating AI-generated code and solutions, examining agent behavior and tool use, comparing model outputs, and developing rubrics and evaluation criteria. It also includes producing evaluation and preference data, maintaining supporting pipelines and infrastructure, synthesizing findings into clear recommendations, and collaborating with researchers and engineers to turn qualitative judgment into scalable processes. This is an independent contractor engagement for approximately three months. The role is remote and open to candidates in North America, LATAM, or India. The preferred availability is 40 hours per week, with at least six hours of Pacific Time overlap. The start is as soon as possible. Compensation is market rate; applicants are asked to provide a specific hourly rate expectation.
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.
Nice To Haves
- Experience with LLM evaluation, coding agents, RLHF, preference data, rubric design, or post-training; these are a plus but not required.
Responsibilities
- Evaluate AI-generated code and solutions across real-world software repositories.
- Review 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 high-quality 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 for the team.
- 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
