Computer Science Benchmark Author and Reviewer AI Research

Develop and validate rigorous academic assessment content that supports an AI research initiative. This role focuses on creating gold-standard computer science benchmarks, evaluating solution quality, and ensuring questions are technically accurate, clear, and appropriately challenging.

• Complete either question-authoring or question-verification assignments in your computer science specialty.
• For authoring assignments, create original, challenging multiple-choice questions, assess their difficulty, and submit them for review.
• Test deep conceptual understanding rather than surface-level recall.
• Ensure every question is self-contained, unambiguous, and precisely defined, with all necessary information included in the prompt.
• Classify question difficulty as Medium, suitable for introductory undergraduate learners, Hard, suitable for advanced undergraduates, or Expert, suitable for post-graduate learners and above.
• Provide one correct answer and nine plausible but subtly incorrect alternatives designed to challenge expert-level solvers.
• Write clear, concise, step-by-step Chain-of-Thought solutions in Markdown.
• Include 1 to 5 academic references per question from reputable sources, such as peer-reviewed journals or university repositories.
• For verification assignments, identify and correct issues involving clarity, completeness, precision, or solvability, and document the rationale for each edit.

• Assignments may cover Accelerator and GPU Kernel Engineering, Formal Methods and Automated Reasoning, Computer Architecture and Accelerators, Distributed Systems, Dev Ops and Site Reliability, Data Engineering and Databases, Cloud and Infrastructure, Operating Systems and Systems Kernels, Machine Learning Engineering, Web and API Development, Embedded Systems Engineering, Computer Graphics and Game Development, or Mobile Engineering.

• PhD or doctoral candidacy in Computer Science, Electrical Engineering, or a closely related field.
• A master''s degree may be considered for candidates with exceptional depth in a specific subdomain.
• Strong graduate-level knowledge of computer science theory, algorithms, systems design, and/or machine learning.
• Research publications, experience at leading technology companies, or a competitive programming background are strong advantages.
• Excellent written English and the ability to communicate complex ideas clearly and concisely.

• Fully remote, asynchronous hourly work.
• Expected commitment of at least 10 hours per week.

Hourly compensation of 66 to 84.