Computer Architecture Researcher Coding Tasks

You will create and review self-contained coding tasks used to evaluate AI models on computer architecture research. The work focuses on practical research questions and technically rigorous evaluations.

• Build hands-on research coding tasks in computer architecture.
• Review AI model outputs in your area and provide technically grounded feedback.
• Work with a project lead to maintain research-quality tasks and evaluations.
• Apply research judgment to coding assignments and use simulator-based evaluation when relevant.
• Work with topics such as caches, prefetchers, branch prediction, and accelerators.
• Evaluate architecture ideas with simulators such as gem5, ChampSim, or comparable tools.

What it pays and takes

This is remote, asynchronous contract work that can fit around ongoing research. Tasks are self-contained and aligned with your research area.

• Pay: $200 per approved task.
• Typical task time: approximately four hours on average.
• Location: Remote; open to candidates in the countries specified for this role.
• Language: Professional fluency in English.
• Required: Published computer architecture research at venues such as ISCA, MICRO, HPCA, ASPLOS, or comparable venues.
• Required: A completed or in-progress PhD in computer science or a related field.
• Required: Strong depth in at least one area such as caches, prefetchers, branch prediction, or accelerators.
• Required: Released research code through GitHub or another research artifact link.
• Required: Ability to produce and assess research code against rigorous technical standards.
• Helpful: First-author publications, Docker experience, reproducible research environments, and experience with gem5, ChampSim, or comparable simulators.

How it works

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

About AI training work

AI training is the human work behind systems that learn from examples, including writing, reviewing, and evaluating model outputs. People with specialized research or technical knowledge help assess difficult tasks and provide the judgment needed to improve these systems.