Remote RL Engineer for AI Training Environments

YO AI Labs; Seattle (WA); Remote; USD 83,000 - 124,000; Part time

Job summary

YO AI Labs is seeking a Senior Software Engineer (Contractor) to support an AI training project remotely at ~15 hours per week. You'll design reinforcement learning environments that evaluate AI models on complex software tasks using Model Context Protocol (MCP) tools.

You will build reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization.

Qualifications

• Proficiency in Python 3, Java, Rust, C++, or TypeScript.
• Strong understanding of algorithms and data structures.
• Experience with bug fixing and debugging complex software issues.
• Proven experience in feature implementation and codebase refactoring.
• Strong knowledge of performance optimization and tuning.
• Excellent written and verbal communication.
• Strong attention to detail.

Responsibilities

• Create reinforcement learning environments for software engineering tasks.
• Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
• Build deterministic verification systems and golden reference solutions.
• Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
• Develop realistic, reproducible software engineering scenarios.
• Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
• Document solutions and provide clear technical feedback.

Skills

Programming languages

Algorithms & DS

Bug fixing

Feature implementation

Code refactoring

Performance tuning

Communication

Job description

YO AI Labs is seeking a Senior Software Engineer (Contractor) to support an AI training project remotely at ~15 hours per week. You'll design reinforcement learning environments that evaluate AI models on complex software tasks using Model Context Protocol (MCP) tools.

You will build reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization.