Software Engineer
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.
- Location: Fully remote.
- Hands-on expertise in at least one of Python, Java, Rust, Go, C++, or TypeScript.
- Tasks: Build challenging coding problems from real repositories, with reproducible environments and verifiers.
Role Details:
- Role Title: Software Engineer.
- Role Type: Contractor (~15 hrs a week).
- Location: Remote.
- 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.
Scope of Work:
- 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.
Preferred Qualifications:
- 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.
