The work
You will review AI-generated Rust code and technical explanations, then help improve them through detailed expert feedback. The work focuses on correctness, idiomatic style, clear reasoning, safety, and following the prompt.
You may also write high-quality Rust solutions and explanations, compare several model responses, and judge which answers are accurate and clear.
- Review Rust code and explanations for correctness and idiomatic style.
- Write Rust solutions and structured technical explanations when needed.
- Evaluate step-by-step reasoning, safety, and prompt adherence.
- Find problems with ownership, borrowing, lifetimes, concurrency, and algorithmic logic.
- Rate and compare multiple AI responses for accuracy and clarity.
What it pays and takes
This is remote, part-time contract work for an intermediate Rust engineer. The role is open to candidates in the listed countries and requires strong English writing skills.
- Pay: $60 per hour.
- Time: 20+ hours per week.
- Location: Open to candidates in Bangladesh, Bhutan, Brazil, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, the Philippines, the United States, Timor-Leste, and Vietnam.
- Language: Fluent English with precise, structured technical writing.
- Experience: 1 to 2+ years of professional Rust development in backend, command-line, or systems work.
- Technical knowledge: Rust ownership, borrowing, lifetimes, memory safety, traits, generics, pattern matching, and error handling.
- Education: Bachelor's degree in Computer Science or a closely related technical field.
- Preferred background: AI data training, code review at scale, large language models, Tokio, Actix, Serde, async Rust, competitive programming, or Rust open-source contributions.
- Additional strengths: Attention to performance, concurrency, and correctness.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work uses human-written examples and expert reviews to improve how artificial intelligence responds. People with strong technical skills are paid to assess model outputs, explain errors, and create reliable examples that help models produce better results.