GPU Kernel Expert
Recruitment Room →GPU Kernel Expert at Recruitment Room is a contract role based in Remote · United States-231 (remote). The listing states pay of $145,600–$187,200 and asks for 3–15 yrs of experience. Listed skills: GPU/accelerator kernels. It was published on 27 August 2026 and was open at last check.
| Role | GPU Kernel Expert |
|---|---|
| Company | Recruitment Room |
| Location | Remote · United States-231 (remote) |
| Employment type | Contract |
| Pay (as listed) | $145,600–$187,200 |
| Experience asked | 3–15 yrs |
| Skills listed | GPU/accelerator kernels |
| Published | 27 August 2026 |
| Status | Open at last check |
GPU Kernel Expert
Remote | Independent Contractor | United States | $145,600–$187,200 annualized ($70–$90/hour)
About the Role
Apply your GPU kernel development and optimization expertise to help improve the capabilities of advanced AI systems.
As a GPU Kernel Expert, you’ll evaluate GPU and accelerator kernel development tasks used to train and assess frontier AI models. You’ll assess numerical correctness, performance benchmarking, task scope, compilation, and runtime behavior across a range of kernel development scenarios.
Your technical judgment will help ensure that AI training and evaluation tasks accurately reflect real-world GPU and accelerator engineering challenges.
What You’ll Do
- Evaluate GPU and accelerator kernel tasks for quality, correctness, completeness, and technical rigor.
- Assess numerical correctness using appropriate absolute, relative, and ULP tolerance criteria.
- Evaluate whether reference implementations are appropriate and reliable for validating kernel outputs.
- Review performance benchmarks for fairness, consistency, and methodological soundness.
- Assess task scope and determine whether requirements are technically clear, realistic, and appropriately defined.
- Evaluate compilation and runtime behavior across different hardware and software environments.
- Identify common failure modes, including: Driver and environment mismatches
- Out-of-memory (OOM) conditions
- Kernel launch configuration errors
- Shape and stride mismatches
- Autotuning failures
- Provide clear, structured, rubric-based written feedback.
- Evaluate kernel tasks involving generation, translation, migration, debugging, optimization, and operator fusion.
What You Bring
- 3+ years of hands-on experience developing, optimizing, or verifying GPU or accelerator kernels.
- Professional experience with at least two of the following: CUDA
- Triton
- NKI
- Pallas (JAX)
- Strong understanding of numerical correctness for GPU kernels, including: Absolute and relative tolerances
- ULP-based comparisons
- Reference implementation selection
- Demonstrated experience with performance profiling and benchmarking using tools or methodologies such as: NVIDIA Nsight
- Nsight Compute (NCU)
- Roofline analysis
- Framework-native profilers
- Familiarity with common GPU/kernel compilation and runtime failure modes.
- Experience with at least three of the following kernel task types: Generation from specification
- Translation or lowering across frameworks
- Migration between hardware targets
- Kernel debugging
- Performance optimization
- Operator fusion
- Strong analytical skills and attention to technical detail.
- Ability to communicate complex kernel engineering concepts clearly in writing.
Preferred Qualifications
Experience in the following areas is highly valuable:
- Experience across both NVIDIA GPU ecosystems such as CUDA/Triton and custom accelerator ecosystems such as NKI/Pallas/TPU.
- Background in compiler engineering, MLIR, or intermediate-representation lowering.
- Deep understanding of memory-hierarchy optimization, including: Shared-memory tiling
- Register pressure
- Bank conflicts
- Memory coalescing
- Contributions to GPU or accelerator kernel libraries and related open-source projects.
- Experience with technologies such as cuBLAS, cuDNN, Triton community kernels, or JAX/XLA custom calls.
Compensation & Engagement
- Rate: $70–$90/hour
- Annualized Equivalent: $145,600–$187,200
- Location: United States
- Work Arrangement: Fully remote
- Engagement Type: Independent contractor
- Schedule: Flexible
- Payment: Weekly via Stripe or Wise
Annualized compensation is based on 2,080 hours per year for comparison purposes only. Actual earnings depend on the number of hours and projects completed.
Why This Opportunity?
- Apply your GPU and accelerator engineering expertise to advanced AI development.
- Work on technically challenging kernel evaluation and optimization problems.
- Help improve how AI systems understand low-level performance, numerical correctness, and hardware acceleration.
- Evaluate realistic engineering scenarios across GPUs, accelerators, frameworks, and compilers.
- Work remotely with a flexible schedule.
- Contribute specialized expertise to high-impact AI training and evaluation projects.
Contract & Payment Terms
- You will be engaged as an independent contractor.
- Work is fully remote and can be completed on your own schedule.
- Projects may be extended, shortened, or concluded early depending on project needs and performance.
- Your work will not require access to confidential or proprietary information belonging to any employer, client, or institution.
- Payments are made weekly via Stripe or Wise based on services rendered.
- H-1B and STEM OPT candidates cannot be supported at this time.
Equal Opportunity
All qualified applicants will be considered without regard to legally protected characteristics. Reasonable accommodations are available upon request.
Create a free OnJob profile to apply and see your AI match score before you apply. · Posted 27 Aug 2026.
GPU Kernel Expert at Recruitment Room — questions answered
What does the GPU Kernel Expert role at Recruitment Room pay?
The GPU Kernel Expert at Recruitment Room listing states pay of $145,600–$187,200 for the Remote · United States-231 (remote) position. That figure is taken directly from the employer's own posting as published, not estimated or averaged from other roles, and the same listing asks for 3–15 yrs of experience.
Is the GPU Kernel Expert role at Recruitment Room remote?
Yes — Recruitment Room advertises this GPU Kernel Expert role as remote, tied to Remote · United States-231, and it is listed as contract work. Remote terms come from the employer's own posting, so confirm the expected working hours, timezone and any on-site days with Recruitment Room before you apply.
What skills does the GPU Kernel Expert role at Recruitment Room require?
The GPU Kernel Expert at Recruitment Room listing names GPU/accelerator kernels. Those are the skills the employer put on the posting itself, so they are the ones worth matching in your profile and covering first in an interview.
How much experience do you need for the GPU Kernel Expert role at Recruitment Room?
Recruitment Room asks for 3–15 yrs of experience on this GPU Kernel Expert posting, alongside GPU/accelerator kernels. Employers commonly consider candidates slightly under a stated band when the listed skills line up.
Is the GPU Kernel Expert role at Recruitment Room still open?
The GPU Kernel Expert posting at Recruitment Room was open at OnJob's last check of the employer's careers page, having been published on 27 August 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
How do you apply for the GPU Kernel Expert role at Recruitment Room?
Apply to the GPU Kernel Expert at Recruitment Room role through OnJob with a free profile: OnJob scores your fit against the listing, shows the skills lowering that score, and submits an ATS-ready profile. Creating a profile is free and needs no card.
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