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Software Engineer Reinforcement Learning Environment Evaluator

Evaluate how AI models solve complex software engineering problems by designing reproducible reinforcement learning environments, verification systems, and coding tasks. Remote, part-time contractor work pays $50–$100 per hour for less than 20 hours weekly.

OpenTrain AI

Coding & Software

100% Remote Hourly · $50–$100/hr

$50–$100/hr

Compensation

Worldwide

Eligibility

Entry

Experience

Jul 23, 2026

Posted

Open worldwide

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About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people discover specialized projects, build a credible AI training profile, and apply for opportunities that support long-term growth. Creating an OpenTrain account is free.

About AI Training Work

AI training is the human side of building modern artificial intelligence. Experts create tasks, review model behavior, and define reliable standards so AI systems can solve real-world problems more accurately and safely.

This fully remote work offers a flexible way to contribute to cutting-edge AI development while applying skills from software engineering and technical problem-solving.

The Role

OpenTrain is seeking a Software Engineering Reinforcement Learning Environment Evaluator to support AI training focused on software engineering model evaluation. You will create environments that measure how AI models solve complex engineering problems and use Model Context Protocol tools effectively.

Prior AI training experience is not required. Strong real-world software engineering knowledge is the most important qualification for this role. This is an entry-level, part-time contractor opportunity available worldwide for English-speaking contributors.

  • Contractor and part-time opportunity
  • Less than 20 hours per week
  • Remote and worldwide
  • English-language work
  • Pay: $50–$100 USD per hour

What You'll Do

You will design reproducible environments, deterministic verification systems, and golden reference solutions that provide consistent assessments of software engineering ability. Your work will help make AI model evaluations precise, repeatable, and meaningful.

Assignments may involve working with real MCP servers, creating tasks that require models to discover and reason over information, and documenting evaluation criteria that other reviewers and engineers can apply consistently.

  • Design reinforcement learning environments for software engineering tasks
  • Create deterministic verification and golden reference solutions
  • Fix bugs, implement features, and refactor codebases
  • Optimize software performance and scalability
  • Develop tasks involving information discovery through real MCP servers
  • Document clear evaluation criteria
  • Help maintain reliable and consistent assessments

Required Skills

You should be proficient in at least one of C++, Python, Java, Go, TypeScript, or Rust. The role requires strong software engineering judgment and the ability to apply core engineering principles to complex evaluation environments.

Experience with large-scale or distributed codebases, rigorous code review, software best practices, or modern AI and machine learning systems is helpful but not required.

  • Proficiency in at least one of C++, Python, Java, Go, TypeScript, or Rust
  • Strong understanding of algorithms and data structures
  • Ability to debug issues, implement features, and refactor codebases
  • Ability to apply performance tuning to complex software
  • Judgment in designing deterministic verification systems
  • Ability to create maintainable engineering solutions
  • Strong written and verbal communication
  • Attention to detail and effective remote collaboration

Why This Work Matters

Every major AI system depends on people who prepare examples, evaluate outputs, and define what good performance looks like. In this role, your engineering expertise will directly shape how AI models reason about software development and interact with technical tools.

OpenTrain helps you build a durable AI training portfolio by giving you a place to showcase relevant experience, discover projects aligned with your skills, and grow in a rapidly expanding field.

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