For PhD-level researchers and research engineers who publish and ship code.

Domain: ML Systems and GPU Kernels (CUDA, Triton and CUTLASS kernels, inference serving and ML compilers)

The work

Hands-on research coding in your own area, close to the work you already do. Each task is self-contained, and the project lead walks you through the full scope and a worked example once you're onboarded. Work is asynchronous, so you can fit it around your own research.

Application process

Candidates who meet the requirements and provide the requested materials will be prioritised for review. As part of this process we conduct thorough background checks. Please apply only if you meet these requirements.

Why apply

• Hands-on research coding in your own field.
• Fully remote, asynchronous and flexible.
• $200 per approved task, about 4 hours each.

• Build technical research coding tasks in ML systems and GPU kernels.
• Review and give feedback on AI model outputs in your area.
• Work with the project lead to keep tasks at research quality.

Requirements

• Experience: published research with released code in ML systems and GPU kernels.
• Education: PhD in CS or a related field, completed or in progress.
• Published research at venues such as MLSys, OSDI, SOSP, PPoPP or SC, or comparable.
• Released research code (GitHub or artifact link).
• PhD in computer science or a related field, completed or in progress.
• Meets the experience and education bar described in Full Description.

Preferred qualifications

• First-author publications in your area.

Work arrangement: Fully remote

$50/hr.

$200 per approved task, about 4 hours each ($50/hr equivalent).