Senior AI Software Engineer — RL Environments (Remote)

YO AI Labs; Seattle (WA); À distance; USD 41 000 - 68 000; Temps partiel

Résumé du poste

YO AI Labs is seeking a Senior Software Engineer on a contracting basis (≈15 hours/week) to support an AI training project by building reinforcement learning environments for software engineering tasks using MCP tools.

You will design reproducible environments, deterministic verification, and reference solutions for bug fixing, feature development, codebase refactoring, and performance optimization, with emphasis on clean interfaces and reliable feedback.

Qualifications

• Strong 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.

Responsabilités

• 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.

Connaissances

Python

Java

Rust

C++

TypeScript

Description du poste

YO AI Labs is seeking a Senior Software Engineer on a contracting basis (≈15 hours/week) to support an AI training project by building reinforcement learning environments for software engineering tasks using MCP tools.

You will design reproducible environments, deterministic verification, and reference solutions for bug fixing, feature development, codebase refactoring, and performance optimization, with emphasis on clean interfaces and reliable feedback.