jobapplierAWS Trainium / NKI Kernel Expert
- Remote · Argentina
- Remote
- $65 /hr
- Senior Level
- Posted
Responsibilities
- 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
- 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
Requirements
- 2+ years of hands-on experience
Preferred
- 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
What You’ll Work On
Tile-based computation and DMA scheduling rather than simply translated from GPU-based approaches.
What We’re Looking For
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
Familiarity with
nki.language
- @nki.jit, or XLA custom calls
- Experience with technical evaluation, AI/ML data projects, RLHF, or rubric-based assessment
- Engagement
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.