Remote Software Engineer - Python/Typescript
About The Position
Turing is seeking experienced, hands-on software engineers to evaluate and improve AI coding models. Rather than primarily building production applications, the role involves working with coding agents across real-world repositories and assessing the quality of their work. You will review generated code and agent behavior, determine whether solutions are technically correct, identify failure modes, and create evaluation signals and feedback to improve model performance. This includes assessing whether an agent understood a task, selected an appropriate approach, and produced code that is correct, robust, and maintainable, then clearly explaining where it succeeded or failed. The role also involves creating and refining evaluation rubrics, producing evaluation and preference data, and building and maintaining pipelines and infrastructure for data generation, collection, and evaluation workflows. You will synthesize findings into clear updates and recommendations and collaborate with researchers and engineers to turn qualitative judgment into scalable processes. This is an independent contractor engagement of approximately three months, with 40 hours per week preferred and at least six hours of Pacific Time overlap. The position is open to candidates in North America, LATAM, or India.
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 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
