AWS Trainium / NKI Kernel Expert

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. We’re looking for engineers with hands-on experience building or optimizing **NKI kernels on AWS Trainium or Inferentia2 hardware** who understand how Trainium’s architecture differs from traditional GPU programming. ## 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.