AWS Trainium / NKI Kernel Expert

Anyone AI; United States; Remote; CLP 81,919,000 - 163,837,000; Part time

Benefits offered by this job

Remote work

Part-time engagement

Focus on Trainium/NKI kernel tech

Job summary

Anyone AI Inc. is seeking experienced AWS Trainium/NKI kernel engineers to evaluate and improve kernel development for AI workloads. You will assess correctness, idiomatic usage, and performance on Trainium hardware.

Youll work remotely on a part-time, project-based engagement, reviewing CUDA→NKI migrations, memory hierarchies (SBUF, PSUM, HBM), tile-based computation, and DMA scheduling, providing clear written feedback.

Qualifications

• 2+ years hands-on experience developing or optimizing NKI kernels.
• Experience with AWS Trainium and/or Inferentia2.
• Strong understanding of tile-based computation, memory hierarchies (SBUF/PSUM/HBM), and DMA.
• Ability to evaluate CUDA→NKI migrations and optimize for Trainium.
• Excellent written feedback on complex kernel implementations.

Responsibilities

• Review and evaluate tasks involving NKI kernels and Trainium-specific patterns.
• Assess correctness and idiomatic optimization for Trainium hardware.
• Benchmark and profile workloads, identify bottlenecks and improvements.
• Provide clear written evaluations and recommendations.

Skills

NKI kernel development

Trainium optimization

CUDA migration evaluation

Profiling workloads

Technical feedback

Tools

AWS Neuron SDK

Neuron Compiler

CUDA

Triton

Job description

Anyone AI is recruiting experienced AWS Trainium / Neuron Kernel Interface (NKI) engineers for a specialized project focused on evaluating and improving kernel development tasks for AI workloads.

What You’ll Work On

You’ll review and evaluate technical tasks involving:

• NKI kernel correctness and Trainium-specific development patterns
• CUDA → NKI kernel migrations
• Trainium performance optimization and benchmarking
• Memory management across SBUF, PSUM, and HBM
• Tile-based computation and DMA scheduling
• Cross-platform numerical correctness between CUDA/Triton and NKI
• Trainium-specific performance bottlenecks and optimization opportunities
• Technical feedback and quality assessment of kernel implementations

The work involves determining whether implementations are not only technically correct, but also idiomatic and optimized for Trainium hardware rather than simply translated from GPU-based approaches.

What We’re Looking For

• 2+ years of hands-on experience developing or optimizing kernels with the Neuron Kernel Interface (NKI)
• Experience working with AWS Trainium and/or Inferentia2
• Strong understanding of:
• Tile-based computation
• SBUF / PSUM / HBM memory hierarchy
• Partition dimension constraints
• DMA orchestration
• Trainium-specific optimization techniques
• Ability to evaluate CUDA → NKI migrations
• Experience profiling and optimizing workloads on Trainium
• Understanding of numerical differences across GPU and Trainium backends
• Strong ability to analyze complex technical implementations and provide clear written feedback

Nice to Have

• Experience with the AWS Neuron SDK or Neuron Compiler
• CUDA or Triton kernel development experience
• Knowledge of NeuronCore-v2 architecture
• Experience with FP32, BF16, FP8, and INT8 workloads
• Experience benchmarking workloads on Trn1 or Trn2 instances
• Familiarity with nki.language, @nki.jit, or XLA custom calls
• Experience with technical evaluation, AI/ML data projects, RLHF, or rubric-based assessment

Engagement

Work Type: Remote

Engagement: Part-time, project-based consulting

Focus: AWS Trainium / NKI kernel engineering and technical evaluation

This is a strong fit for engineers who have worked deeply with AWS Trainium infrastructure and low-level ML kernel optimization and are interested in applying that expertise to technically challenging AI projects.