Audit GPU kernel tasks for memory allocation bugs, execution bottlenecks and parallel-logic errors, confirming they are solvable and reproducible. Suits engineers with deep CUDA or Triton kernel development experience.
Sobre la vacante
Project Overview We are sourcing experienced technical specialists in GPU Kernels to audit tasks used to train and evaluate AI systems. The objective of this project is to ensure that AI training workflows and tasks are technically rigorous, practical, and highly accurate within your specific area of expertise.
Project Deliverables & Scope
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Task Evaluation: Assess whether GPU kernel tasks are technically accurate, realistic, solvable, reproducible, and supported by reliable tests and evaluation criteria.
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Technical Auditing & Feedback: Provide clear, actionable feedback on any identified memory allocation bugs, execution bottlenecks, or parallel computing logic errors within the tasks.
Required Expertise
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Demonstrable professional experience and deep technical knowledge in GPU Kernel development (including CUDA/Triton programming, parallel computing, and hardware-level performance optimization). (Note: Candidates will be considered for one specialty based on their experience; expertise across other domains is not required).
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Strong analytical and problem-solving skills to rigorously test, troubleshoot, and evaluate complex technical scenarios.
We offer a pay rate of $60 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. As a contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply.
Workplace type: Remote
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