Parallel Algorithms And HPC Researcher Coding Tasks

The work

You will create self-contained technical research coding tasks in parallel algorithms and high-performance computing. You will also review AI model outputs and give feedback based on your specialist knowledge.

Tasks should use methods and systems relevant to your published work. You will work with a project lead to maintain research-level quality while organizing tasks around your existing research activities.

• Build technical coding tasks in parallel algorithms and HPC.
• Review AI model outputs in a specialized computing domain.
• Provide clear, expert feedback on technical responses.
• Create tasks grounded in your published research and released code.
• Work asynchronously around ongoing research commitments.

What it pays and takes

This is paid remote contract work. The role is intended for researchers and research engineers with practical experience writing research code and assessing technical AI outputs.

• Pay: $200 per label.
• Work arrangement: Remote contract work with asynchronous scheduling.
• Location: Open to candidates in the countries listed for this role.
• Language: Professional fluency in English.
• Completed or in-progress PhD in computer science or a related field.
• Published research in parallel algorithms and high-performance computing.
• Research presented at venues such as SC, PPoPP, IPDPS, SPAA, ICS, or comparable venues.
• Research code released through GitHub or another research artifact link.
• Practical ability to write research code and assess technical AI model outputs.

Helpful background

The following experience is valuable for this work, although it is not listed as a required qualification.

• First-author publications.
• Depth in MPI, OpenMP, sparse linear algebra, parallel graph algorithms, or GPU solvers.
• Comfort with Docker and reproducible research environments.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind modern AI systems, including writing coding examples and reviewing model responses. Experienced researchers are needed for specialized tasks because their expertise helps assess whether technical outputs are accurate and useful.