AI GPU Kernel Engineer: Performance & Validation

Obsidian; Chicago (IL); On-site; USD 120,000 - 180,000; Full time

Job summary

Obsidian in Chicago seeks a specialist to evaluate GPU/accelerator kernel development tasks used to train frontier AI models. You will judge numerical correctness, performance benchmarks, task scoping, and compile/run validity across diverse kernel task types.

This role demands rubric-based written feedback and clear guidance to improve kernels, with emphasis on cross-framework translation and hardware-target migrations.

Qualifications

• 3+ years hands-on experience developing, optimizing, or verifying GPU kernels in at least two of CUDA, Triton, NKI, or Pallas (JAX).
• Strong understanding of numerical-correctness criteria for kernels (absolute/relative/ULP tolerances, reference-implementation selection).
• Experience with performance profiling and benchmarking (nsight, ncu, roofline analysis, or framework-native profilers).
• Familiarity with common compilation/runtime failure modes (driver mismatches, OOM, launch-configuration errors, shape/stride mismatches, autotuning failures).
• Experience with at least three kernel task types: generation from specification, translation/lowering across frameworks, migration between hardware targets, debugging, performance optimization, or operator fusion.

Skills

CUDA

Triton

NKI

Pallas (JAX)

Performance profiling

Tools

Nsight

NCU

Job description

Obsidian in Chicago seeks a specialist to evaluate GPU/accelerator kernel development tasks used to train frontier AI models. You will judge numerical correctness, performance benchmarks, task scoping, and compile/run validity across diverse kernel task types.

This role demands rubric-based written feedback and clear guidance to improve kernels, with emphasis on cross-framework translation and hardware-target migrations.