Senior Software Engineer for AI Model Training

Contribute expert software engineering work to create reproducible tasks and reference solutions that help train next generation AI systems. You will design Reinforcement Learning environments that test an AI model''s ability to fix code, add features, refactor, and optimize performance, and you will provide the golden reference solution and technical rationale for each task.

• Create reproducible code problems and golden reference solutions that evaluate a model''s software engineering abilities, including bug fixes, feature implementation, refactoring, and performance optimization.
• Contribute expert-level code samples, debugging strategies, and development insights in languages such as Python3, Java, Rust, Go, C++, or TypeScript.
• Analyze, troubleshoot, and resolve complex software defects and performance bottlenecks across diverse codebases.
• Implement new features with attention to scalability, maintainability, and software best practices.
• Refactor and modernize legacy code to improve clarity, efficiency, and long-term reliability.
• Document technical reasoning, solution approaches, and code decisions to improve the quality of AI training data.
• Review and validate peer-contributed code and technical submissions for accuracy and clarity.

• Significant hands-on expertise in at least one of the following: Python3, Java, Rust, Go, C++, or TypeScript.
• Solid understanding of algorithms, data structures, and core software engineering principles.
• Proven ability to debug complex systems, resolve bugs, and deliver effective performance optimizations.
• Experience with large codebase refactoring and legacy system modernization is preferred.
• Track record of delivering high-impact features from conception through delivery within cross-functional projects.
• Strong documentation and communication skills to articulate technical concepts clearly.
• No prior AI experience required, interest in AI and its technical challenges is a plus.

• Engagement type: Contractor, independent contractor relationship.
• Typical commitment: approximately 15 hours per week.
• Location: Remote.
• Output expectations: compensation is output based, experts are paid per task that meets project specifications. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
• Availability: roles are typically filled within 48 hours and selected experts are expected to start their first tasks within 24 to 48 hours after completing onboarding.

Pay range: $50 - $150 per hour. Payment is task based and tied to deliverables that meet project specifications. The time required to complete tasks will vary by expert and workflow.

• Applicants must have clear open source contributions and public profiles to demonstrate experience, for example GitHub or GitLab repositories.
• Preferred syntax familiarity includes C++, Python, Java, Go, TypeScript, or Rust, and demonstrated experience with bug fixing, feature implementation, codebase refactoring, and performance optimization.
• How to apply: complete the online application and screening questions, complete an AI interview of approximately 30 minutes, complete a technical assessment if requested, and await hiring manager review.
• If selected, expect to complete onboarding and begin accepting tasks within 24 to 48 hours.