Remote AI Training Architect for Software Tasks

YO AI Labs; New York (NY); Remote; USD 35,000 - 65,000; Part time

Job summary

YO AI Labs is seeking a Senior Software Engineer to support an AI training project. This contractor role offers about 15 hours per week and is fully remote, giving you flexibility to work from anywhere while contributing to high-impact tasks.

You will design reproducible reinforcement learning environments, create reference solutions, and verify tasks that evaluate coding ability, problem-solving, and tool usage across complex codebases.

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.

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

Debugging

Feature implementation

Codebase refactoring

Performance optimization

Communication

Detail-oriented

Job description

YO AI Labs is seeking a Senior Software Engineer to support an AI training project. This contractor role offers about 15 hours per week and is fully remote, giving you flexibility to work from anywhere while contributing to high-impact tasks.

You will design reproducible reinforcement learning environments, create reference solutions, and verify tasks that evaluate coding ability, problem-solving, and tool usage across complex codebases.