Senior Kernel Engineer

Primary

Skills:

• CUDA programming (advanced)
• Triton optimization (advanced)
• Profiling tools (advanced)
• Debugging kernels (advanced)
• Performance tuning (advanced)

Contract Type: W2

Duration: 3+ months with possible extension or conversion

Location: Bellevue, WA (#LI-Onsite)

Pay Range: $85.00 - $90.00 Per hour on W2 #LP

This role involves the low-level development and optimization of compute kernels for AI accelerator hardware. You will ensure training environments accurately mirror real-world kernel engineering challenges by writing, debugging, and optimizing operators. A key aspect of this position is using profiling tools and accelerator programming interfaces to validate task realism and define solution quality.

• Develop and optimize custom compute kernels for AI accelerators.
• Validate training environment tasks for realistic kernel development scenarios.
• Debug and profile kernel code to identify and resolve performance issues.
• Analyze kernel performance against hardware constraints and memory hierarchy.
• Consult with training environment development teams on task realism and quality.

• Computer Science, Computer Engineering, Electrical Engineering, or equivalent technical degree and 7+ years of relevant experience is required.
• Direct experience with AWS Trainium/Inferentia and the Neuron Kernel Interface (NKI) and Hands-on proficiency with a low-level kernel programming language such as CUDA, Triton, or the AWS Neuron Kernel Interface (NKI).
• Familiarity with the Neuron SDK, Neuron Profiler, and framework integration (PyTorch, JAX).
• Experience porting kernels between accelerator backends (e.g., CUDA/Triton to NKI) and understanding of deep learning operator implementations (attention, GEMM, normalization).

Experience in developing and optimizing low-level code for AI accelerators is essential, with a strong preference for experience with Triton over CUDA.