Trainium NKI Kernel Expert — Remote Part-Time

Anyone AI; United States; On-site; USD 83,000 - 138,000; Part time

Job summary

anyone-ai is seeking a remote, part-time consultant to evaluate and refine AWS Trainium and Neuron Kernel Interface tasks for AI workloads. The role requires deep kernel experience and low-level optimization.

You will review NKI kernel correctness, CUDA-to-NKI migrations, memory hierarchies, and DMA scheduling, delivering structured technical feedback and opportunities for optimization.

Qualifications

• Two or more years of hands-on experience developing or optimizing kernels with the Neuron Kernel Interface.
• Experience with AWS Trainium and/or Inferentia2 hardware.
• Strong grasp of tile-based computation, SBUF/PSUM/HBM memory hierarchy, partition dimension constraints, and DMA orchestration.
• Ability to evaluate CUDA-to-NKI migrations critically.
• Background profiling and optimizing workloads on Trainium.
• Understanding of numerical differences across GPU and Trainium backends.

Responsibilities

• Review NKI kernel correctness and Trainium-specific development patterns.
• Evaluate CUDA-to-NKI kernel migrations for idiomatic Trainium implementation.
• Assess performance optimization and benchmarking on Trainium hardware.
• Review memory management across the SBUF, PSUM, and HBM hierarchy.
• Analyze tile-based computation and DMA scheduling decisions.
• Evaluate cross-platform numerical correctness between CUDA/Triton and NKI.
• Identify Trainium-specific bottlenecks and surface optimization opportunities.
• Provide structured written technical feedback and quality assessments.

Skills

NKI kernel development

Trainium hardware experience

Memory hierarchy optimization

CUDA-to-NKI migrations evaluation

Performance profiling

Tools

AWS Neuron SDK

Neuron Compiler

Job description

anyone-ai is seeking a remote, part-time consultant to evaluate and refine AWS Trainium and Neuron Kernel Interface tasks for AI workloads. The role requires deep kernel experience and low-level optimization.

You will review NKI kernel correctness, CUDA-to-NKI migrations, memory hierarchies, and DMA scheduling, delivering structured technical feedback and opportunities for optimization.