Remote Software Engineer - Python/Typescript
About The Position
Turing is hiring an experienced, hands-on software engineer to evaluate and improve AI coding models. The work focuses on coding agents operating across real-world software repositories: reviewing generated code and agent behavior, assessing technical correctness and quality, identifying failure modes, and creating evaluation signals and feedback to improve model performance. The role emphasizes evaluating whether an agent understands a task, chooses an appropriate approach, and produces correct, robust, and maintainable code, and explaining precisely where it succeeds or fails. The engineer will also build and maintain pipelines and infrastructure for data generation, collection, and evaluation workflows. They will collaborate with researchers and engineers to turn qualitative judgment into scalable processes, and communicate findings, updates, and recommendations clearly. This is an independent contractor engagement of approximately three months. The preferred availability is 40 hours per week, with at least six hours of overlap with Pacific Time. The role is open to candidates in North America, LATAM, or India, and the start is as soon as possible. Compensation is market rate; candidates 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.
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 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
