Open role at a frontier AI lab
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Opportunity Snapshot
Pay: $50–100
Time per task: 5 hours for trainers and 1.5 hours for reviewers
Engagement: Project-based — paid per approved task
Commitment: ~15 hours per week
You’ll need: Hands-on expertise in at least one of Python, Java, Rust, Go, C++, or TypeScript
Your tasks: Build challenging coding problems from real repositories, with reproducible environments and verifiers
You’ll create Reinforcement Learning Environments that test a model’s ability to solve real software engineering problems: tracking down subtle bugs, building non-trivial features, refactoring, and optimizing performance. Each task means defining the problem, building a reproducible environment, and writing a reference solution.
• Create realistic, challenging coding tasks for frontier AI models, drawn from repositories you know well.
• Design problems that require real engineering skill — subtle bugs, non-trivial features, meaningful performance work — not lookup or boilerplate.
• Build a reproducible environment for each task.
• Write deterministic verifiers that accept correct solutions across different valid implementations, while rejecting incorrect, incomplete, or hard-coded approaches.
• Provide a reference solution showing how the task can be solved.
• Flag tasks that turn out to be ambiguous or unverifiable rather than submitting them.
• Significant hands-on expertise in at least one of: Python3, Java, Rust, Go, C++, or TypeScript.
• Deep understanding of algorithms, data structures, and software engineering principles.
• Proven ability to debug complex systems, resolve bugs, and deliver effective optimizations.
• Experience with large codebase refactoring and legacy system modernization.
• Track record of delivering high-impact features from conception through delivery.
• Strong documentation and communication skills to articulate technical concepts clearly.
• Interest in AI and its technical challenges — previous AI experience not required.
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required may vary depending on your experience and workflow.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
How the selection process works
• Apply and complete the screening questions
• Complete the AI interview for this role — it’s how your expertise gets in front of the client
• Profile review
• Onboarding — our Talent Ops team will get you set up