GPU Kernel Developer - Fully Remote | Upto $90/hr

mercor; United States; Remote; USD 96,000 - 124,000; Full time

Job summary

Mercor is seeking a GPU Kernel Expert for remote contract work to support AI research teams. You will evaluate GPU/accelerator kernels for training and evaluation, focusing on correctness and performance.

You will collaborate with researchers, review compile/runtime behavior, and provide rubric-based feedback. Requires 3+ years with CUDA/Triton/NKI/Pallas and strong profiling experience.

Qualifications

• 3+ years of experience with CUDA, Triton, NKI, or Pallas (JAX).
• Strong understanding of numerical-correctness criteria for kernels.
• Experience with performance profiling and benchmarking (e.g., nsight, ncu).
• Familiarity with common compilation and runtime failure modes.
• Experience with at least three kernel task types.

Responsibilities

• Evaluate the quality and correctness of GPU/accelerator kernel development tasks for training and evaluating AI models.
• Assess numerical correctness, performance-benchmarking fairness, and task scoping across diverse kernel task types.
• Review compilation and runtime validity, providing clear, rubric-based written feedback.
• Collaborate with AI research teams to improve model training and evaluation processes.
• Work independently and asynchronously to meet deadlines and enhance AI model performance.

Skills

CUDA

Triton

NKI

Pallas (JAX)

Performance profiling

Tools

nsight

ncu

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs.

Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position: GPU Kernel Expert

Type: Contract

Compensation: $70–$90/hour

Location: Remote

Role Responsibilities

• Evaluate the quality and correctness of GPU/accelerator kernel development tasks for training and evaluating AI models.
• Assess numerical correctness, performance-benchmarking fairness, and task scoping across diverse kernel task types.
• Review compilation and runtime validity, providing clear, rubric-based written feedback.
• Collaborate with AI research teams to improve model training and evaluation processes.
• Work independently and asynchronously to meet deadlines and enhance AI model performance .

Qualifications Must-Have

• 3+ years of experience with CUDA , Triton , NKI , or Pallas (JAX) .
• Strong understanding of numerical-correctness criteria for kernels.
• Experience with performance profiling and benchmarking (e.g., nsight , ncu ).
• Familiarity with common compilation and runtime failure modes.
• Experience with at least three kernel task types.

Preferred

• Experience with both NVIDIA GPU and custom-accelerator ecosystems.
• Background in compiler engineering, MLIR , or intermediate-representation lowering.
• Understanding of memory-hierarchy optimization.
• Contributions to kernel libraries like cuBLAS , cuDNN , or Triton .