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About Turing

Turing is one of the world’s leading AGI infrastructure companies, working with frontier AI labs to accelerate model development through high-quality training data, evaluations, and engineering talent.

About the Role

We’re looking for experienced, hands-on software engineers to help evaluate and improve AI coding models.

Rather than primarily building production applications, you’ll work with coding agents across real-world repositories and assess the quality of their work. You’ll review generated code and agent behavior, determine whether solutions are technically correct, identify failure modes, and create the evaluation signals and feedback used to improve model performance.

Think of the coding agent as another engineer whose work you’re reviewing: Can it understand the task? Did it choose the right approach? Is the resulting code correct, robust, and maintainable? Can you explain precisely where it succeeded or failed?

What You’ll Do

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 closely with researchers and engineers to translate qualitative judgment into scalable processes
Share clear, actionable findings with AI researchers and engineers

What We’re Looking For

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

Experience with LLM evaluation, coding agents, RLHF, preference data, rubric design, or post-training is a plus, but not required.

Engagement Details

Compensation: Market rate; please provide a specific hourly rate expectation
Availability: 40 hours/week preferred, with at least 6 hours of Pacific Time overlap
Type: Independent contractor
Duration: Approximately 3 months
Start: As soon as possible

Evaluation Process

AI interview (~25 minutes)
Practical code/AI evaluation exercise (~30 minutes)
Hiring manager interview (~20 minutes)

The practical exercise focuses on your ability to review and evaluate AI-generated code, not competitive programming or algorithm puzzles.

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