Senior Software Engineer for AI Model Training

Create reproducible reinforcement learning environments and golden reference solutions that train and evaluate AI models on realistic software engineering problems. You will contribute expert-level code examples, debugging strategies, and technical explanations that help next-generation AI systems learn to fix bugs, implement features, refactor legacy code, and optimize performance.

• Create Reinforcement Learning environments that test an AI model''s ability to solve complex software engineering tasks, and deliver a reproducible environment plus a golden reference solution for each problem.
• Contribute expert-level code samples and development insights in one or more of these languages: Python3, Java, Rust, Go, C++, or TypeScript.
• Analyze, troubleshoot, and resolve complex software defects and performance bottlenecks across diverse codebases.
• Implement new features that are scalable, maintainable, and aligned with software engineering best practices.
• Refactor and modernize legacy code to improve clarity, efficiency, and long-term reliability.
• Document technical reasoning, solution approaches, and code decisions to produce high-quality AI training data.
• Review and validate peer-contributed code and technical submissions for accuracy and clarity.

• Senior-level software engineering experience with significant hands-on expertise in at least one of: Python3, Java, Rust, Go, C++, or TypeScript.
• Strong understanding of algorithms, data structures, and core software engineering principles.
• Proven ability to debug complex systems, resolve bugs, and deliver performance optimizations.
• Experience performing large codebase refactoring and modernizing legacy systems.
• Track record of delivering features from conception through delivery within cross-functional projects.
• Strong documentation and communication skills to clearly articulate technical concepts.
• Interest in AI and its technical challenges is preferred, prior AI experience is not required.

• Role type, contractor, approximately 15 hours per week.
• Remote work.
• Output-based compensation, experts are paid per task that meets project specifications; time required varies by expert and workflow.
• Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
• Typical hiring cadence fills roles within 48 hours, and selected experts are expected to start their first tasks within 24 to 48 hours of completing onboarding.

Pay range listed as $50 to $150 per hour. Compensation is output-based and paid per completed task that meets project specifications. The actual time to complete tasks may vary by project and expert.

• Applicants must have clear open source contributions and a public profile such as GitHub or GitLab to showcase experience.
• Preferred language experience includes C++, Python, Java, Go, TypeScript, or Rust.

• Submit an application and answer screening questions.
• Complete an AI interview, approximately 30 minutes.
• Complete a technical assessment, tentatively required.
• Final review by the hiring manager.
• If selected, complete onboarding and be prepared to begin work within 24 to 48 hours.

About micro1: micro1 is an AI data lab that converts domain expertise into high-quality training data, evaluations, and feedback loops to improve how AI systems learn, reason, and perform. Experts contribute real-world knowledge across domains to help build the human intelligence layer for frontier AI.