The work
You will help evaluate AI models on difficult technical problems in machine learning inference, GPU kernels, inference serving, and large-model deployment. The work focuses on judging model answers and explaining what strong technical reasoning looks like, rather than building production systems.
- Design realistic technical scenarios and problem sets.
- Write reference solutions and grading rubrics that define correctness, depth, and technical judgment.
- Review AI-generated answers for accuracy, reasoning quality, and understanding of the subject.
- Provide structured feedback and write clear technical explanations of your decisions.
What it pays and takes
- Pay: $100 to $170 per hour.
- Schedule: 20+ hours per week, with flexible, asynchronous work.
- Location: Fully remote, with availability limited to eligible countries.
- Work type: Part-time contractor.
- Language: Strong written English for technical explanations, reference answers, grading rubrics, and feedback.
- Education: A PhD or doctorate, or a master's degree supported by a strong research record.
- Helpful background: Current or recent hands-on work in machine learning inference, GPU kernels, inference serving, kernel optimization, or large-model deployment. Research publications, open-source contributions, recognized work, or experience with code review, peer review, grading, or editing can help.
- Useful tools and systems include SGLang, vLLM, Mamba or Mamba2, TensorRT-LLM, and GPU kernel development.
How it works
OpenTrain is where you find this role and begin your application. Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI systems learn from examples that people create and review. Roles like this pay for specialized expertise to assess difficult technical answers and explain what makes them correct.
Listed by OpenTrain AI. Details can change, so check the original posting before applying. View original posting