Schedule: Flexible, you pick the hours and days (including weekends if desired)
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
As an expert you will be creating Reinforcement Learning Environments which test an AI model’s ability to solve complex software engineering problems using Model Context Protocol (MCP) tools. Tasks may involve fixing bugs, implementing features, refactoring code, or optimizing performance while requiring agents to discover and reason over information from real MCP servers. You will design reproducible environments, deterministic verification, and golden reference solutions that accurately measure both MCP tool use and software engineering ability.
Requirements
Required Skills and Qualifications:
Proficiency in C++, Python, JAVA, GoLang, Typescript, or Rust.
Deep understanding of algorithms, data structures, and performance tuning.
Demonstrated experience in debugging complex software issues and delivering maintainable solutions.
Strong background in feature development and codebase refactoring.
Proven ability to optimize software for performance and scalability.
Exceptional written and verbal communication skills, with a keen attention to detail.
Track record of success in collaborative, cross-functional teams, ideally in remote settings.
Process:
Apply to the role, filling out the screening questions
Complete AI Interview (approx. 30 minutes)
Technical Assessment (Tentative)
Hiring Manager review
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