Senior AI Software Engineer — RL Environments (Remote)

YO AI Labs

Maryland

Remote

USD 96,000 - 193,000

Full time

3 days ago
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Job summary

YO AI Labs is seeking a Senior Software Engineer to create reinforcement learning environments for software engineering tasks using MCP tools. This contractor role (remote, ~15 hours/week) emphasizes reproducible scenarios, deterministic verification, and reference solutions for bug fixes, feature work, refactoring, and performance tuning.

You will document solutions, provide technical feedback, and ensure tasks effectively measure coding ability, problem-solving, and tool usage across languages

Qualifications

  • Strong programming skills in multiple languages including Python, Java, Rust, C++, or TypeScript.
  • Solid understanding of algorithms and data structures.
  • Experience debugging complex software issues and optimizing performance.

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

Python 3
Java
Rust
C++
TypeScript
Algorithms
Data structures
Bug fixing
Code refactoring
Performance optimization
Communication

Tools

MCP tools

Job description

YO AI Labs is seeking a Senior Software Engineer to create reinforcement learning environments for software engineering tasks using MCP tools. This contractor role (remote, ~15 hours/week) emphasizes reproducible scenarios, deterministic verification, and reference solutions for bug fixes, feature work, refactoring, and performance tuning.

You will document solutions, provide technical feedback, and ensure tasks effectively measure coding ability, problem-solving, and tool usage across languages

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