Software Engineer - Python/Typescript

Turing • Seattle, WA

2d

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. The engineer reviews generated code and agent behavior, determines whether solutions are technically correct, identifies failure modes, and creates evaluation signals and feedback to improve model performance. The role requires judging whether agents understand tasks, choose appropriate approaches, and produce correct, robust, maintainable code, and clearly explaining where they succeed or fail.

The engineer will also build and maintain pipelines and infrastructure for data generation, collection, and evaluation workflows; create high-quality evaluation and preference data; and collaborate with researchers and engineers to turn qualitative judgments into scalable processes. This is an independent contractor engagement for approximately three months, with a preference for 40 hours per week and at least six hours of Pacific Time overlap. The role is open to candidates in North America, LATAM, or India, with a start as soon as possible.

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.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed