Hire GPU engineers who speak in kernels.
GPU engineers squeeze performance out of hardware: custom kernels, distributed training and the low-level work that decides your compute bill. HiringEye finds them through the code they've written and vets each one before you meet them.
What a strong GPU engineer does
They write and tune the code closest to the hardware: CUDA and Triton kernels, memory layouts, multi-GPU communication and the profiling that tells them where the time really goes.
WHAT WE LOOK FOR
- CUDA C++ and Triton (OpenAI) kernel development
- Memory hierarchy, occupancy and kernel fusion
- Distributed training with NCCL, FSDP, DeepSpeed or Megatron
- Profiling with Nsight Systems and Nsight Compute
- Mixed precision and numerical stability
- Cluster-level performance and utilisation
The best GPU engineers leave a trail in code, not keywords.
Kernel and framework PRs
Contributions to PyTorch, Triton, CUTLASS and attention-kernel projects.
HPC and research backgrounds
Engineers from scientific computing, simulation and research labs.
Benchmarks and papers
Published performance work and research acknowledgments.
Warm introductions
Referrals from performance engineers they've worked beside.
AI runs Round 1. Our people make the call.
Kernel optimisation reasoning
Why a kernel is slow and what they'd change first.
Memory and parallelism
Occupancy, bandwidth limits and data layout decisions.
Multi-GPU communication
Scaling a training job and finding the communication bottleneck.
Hiring GPU engineers: questions
What does a GPU engineer do?
A GPU engineer writes and optimises code that runs on GPUs, such as CUDA or Triton kernels, and improves training and inference performance through profiling, memory optimisation and multi-GPU communication.
How does HiringEye assess GPU engineers?
Every candidate takes a role-specific AI voice interview and a coding-fundamentals assessment, then an expert reviews the scorecard. We probe kernel optimisation, memory hierarchy and distributed-training reasoning.
How fast can HiringEye find GPU engineers?
For most GPU and CUDA roles, the first ranked shortlist arrives within 48 hours of a locked brief.
Need GPU talent? We know where it sits.
Share the workload and the stack. Pay only when your hire joins.