Senior AI/ML Software Engineer - Remote, Part-Time

YO AI Labs

Phoenix (AZ)

Remote

USD 83,000 - 124,000

Part time

4 days ago
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Job summary

YO AI Labs seeks a Senior Software Engineer on a remote contractor basis (~15 hours/week) to build reinforcement learning environments for evaluating AI models using MCP tools. The role focuses on creating reproducible tasks such as bug fixing, feature development, refactoring, and performance optimization, with no prior AI experience required.

You will design deterministic verification, reference solutions, and real-world coding scenarios while ensuring tasks accurately measure problem-solving

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.
  • Proven experience with feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication; detail-oriented.

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

Skills

Python 3
Java
Rust
C++
TypeScript
Algorithms
Bug fixing
Refactoring
Performance
Communication
Attention to detail

Job description

YO AI Labs seeks a Senior Software Engineer on a remote contractor basis (~15 hours/week) to build reinforcement learning environments for evaluating AI models using MCP tools. The role focuses on creating reproducible tasks such as bug fixing, feature development, refactoring, and performance optimization, with no prior AI experience required.

You will design deterministic verification, reference solutions, and real-world coding scenarios while ensuring tasks accurately measure problem-solving

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