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 — reviewing generated code and agent behavior, determining whether solutions are technically correct, identifying failure modes, and creating 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
Design, refine, and iterate on rubrics and evaluation criteria for preference data
Review and label data with a high quality bar, catching subtle issues others might overlook
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
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
Nice to Have
Experience with LLM evaluation, coding agents, RLHF, preference data, rubric design, or post-training
Engagement Details
Compensation: $100–150/hour
Availability: 20–40 hours/week, with at least 6 hours of Pacific Time overlap/day
Type: Independent contractor
Duration: Approximately 3 months
Start: As soon as possible
Location: North America only
Evaluation Process
AI interview (~25 minutes)
Practical code/AI evaluation exercise (~30 minutes)
Hiring manager interview (~20 minutes)
