Software Engineer - Python/Typescript
About The Position
Turing is seeking an experienced, hands-on software engineer to evaluate and improve AI coding models. The work focuses on interacting 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, assesses technical correctness, identifies failure modes, and creates evaluation signals and feedback to improve model performance. The role also involves developing evaluation rubrics and preference data, supporting data-generation and evaluation infrastructure, and communicating findings to researchers and engineers. The engagement is an independent contractor position for approximately three months. The preferred availability is 40 hours per week, with at least six hours of overlap with Pacific Time. The location must be 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 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
