GPU Kernel Engineer – CUDA, Triton & Accelerator Performance

The role

You will review, debug, and evaluate high-performance compute kernels used in AI workloads. The role involves assessing kernel implementations for technical correctness, efficiency, and optimization for target hardware.

What you will do

• Reviewing GPU and accelerator kernel implementations for correctness
• Comparing outputs against reference implementations
• Evaluating numerical tolerance thresholds
• Reviewing kernel benchmarks and determining whether comparisons are fair
• Identifying performance bottlenecks and optimization opportunities
• Assessing whether performance targets are realistic given hardware limits
• Reviewing kernel translations and hardware migrations
• Identifying compilation, driver, memory, shape, and runtime issues
• Determining whether technical tasks are genuinely difficult or incorrectly configured
• Providing clear, actionable technical feedback

Required qualifications

• 3+ years of hands-on experience developing, optimizing, or debugging GPU or accelerator kernels
• Strong experience with at least two of the following: CUDA, Triton, NKI / AWS Neuron, Pallas / JAX
• Strong understanding of GPU performance optimization
• Experience with kernel profiling tools such as Nsight, NCU, roofline analysis, or framework-native profilers
• Understanding of memory bandwidth, compute throughput, GPU occupancy, shared memory, register pressure, memory coalescing, and bank conflicts
• Strong understanding of floating-point numerical correctness and tolerance thresholds
• Experience debugging kernel compilation and runtime issues
• Ability to distinguish software defects, environment problems, and genuine optimization challenges

Nice to have

• Experience across both NVIDIA GPU and custom accelerator ecosystems
• Experience with AWS Trainium, TPU, JAX, or other accelerators
• Compiler engineering experience
• Familiarity with MLIR, XLA, or intermediate representation lowering
• Contributions to GPU or ML kernel libraries
• Experience with cuBLAS, cuDNN, Triton community kernels, or JAX/XLA custom calls
• Experience with AI model evaluation, RLHF, or technical benchmark development

About the company

Anyone AI is recruiting experienced GPU Kernel Engineers for a specialized project.