Senior AI Software Engineer - Remote RL Environments

YO AI Labs; Atlanta (GA); À distance; USD 55 000 - 110 000; Temps partiel

Résumé du poste

YO AI Labs is seeking a Senior Software Engineer contractor to join an AI training project. You will create reinforcement learning environments that evaluate AI models on software engineering tasks using MCP tools, focusing on reproducible environments and deterministic verification.

The role emphasizes bug fixing, feature implementation, refactoring, and performance optimization across large codebases. Remote work with ~15 hours per week and minimal onboarding timeline.

Qualifications

• Experience designing reinforcement learning environments for software tasks.
• Strong proficiency in Python, Java, Rust, C++, or TypeScript.
• Experience with bug fixing and debugging complex software issues.
• Proven ability to implement features and refactor large codebases.
• Strong knowledge of performance optimization and tuning.

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 using MCP tools.
• Develop realistic, reproducible software engineering scenarios.
• Document solutions and provide clear technical feedback.

Connaissances

Python

Java

Rust

C++

TypeScript

Algorithms & DS

Bug fixing

Feature implementation

Code refactoring

Performance optimization

Communication

Attention to detail

Outils

MCP tools

Description du poste

YO AI Labs is seeking a Senior Software Engineer contractor to join an AI training project. You will create reinforcement learning environments that evaluate AI models on software engineering tasks using MCP tools, focusing on reproducible environments and deterministic verification.

The role emphasizes bug fixing, feature implementation, refactoring, and performance optimization across large codebases. Remote work with ~15 hours per week and minimal onboarding timeline.