About this opportunity
Confidential lists this NKI Kernel Developer for AI Model Evaluation opportunity in Berkeley, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Role Overview
Evaluate Neuron Kernel Interface, NKI, development tasks used to train and assess advanced AI models. You will review CUDA-to-NKI migrations, Trainium-focused performance optimizations, and cross-platform numerical correctness, then deliver clear written feedback using defined rubrics.
Key Responsibilities
Assess NKI kernel-development tasks for quality, correctness, and suitability for AWS Trainium and Inferentia2 hardware.
Evaluate the fidelity of CUDA-to-NKI migrations.
Review Trainium-specific performance optimization quality.
Evaluate numerical-correctness standards across GPU and Trainium platforms.
Provide clear, rubric-based written feedback.
Qualifications
At least 2 years of hands-on experience developing or optimizing NKI kernels for AWS Trainium or Inferentia2 hardware.
Strong knowledge of tile-based computation, SBUF, PSUM, and HBM memory-hierarchy management, partition-dimension constraints, and DMA orchestration.
Experience evaluating CUDA-to-NKI migration quality.
Familiarity with Trainium performance profiling, including NeuronCore pipeline utilization, tensor-engine throughput, and memory-bandwidth bottlenecks.
Experience establishing or assessing cross-platform numerical-correctness standards, including GPU versus Trainium accumulation order, rounding behavior, and mixed-precision semantics.
Preferred Qualifications
Experience with the AWS Neuron SDK, Neuron Compiler internals, or NKI kernel-library contributions.
Prior CUDA or Triton kernel-development experience.
Familiarity with NeuronCore-v2 architecture, on-chip SRAM topology, and FP32, BF16, FP8, and INT8 data types.
Experience benchmarking machine-learning training workloads on Trn1 or Trn2 instances.
Work Terms
Remote role, open to candidates located in the United States.
Hourly engagement.
Compensation
$70 to $90 per hour.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.