Senior ML Kernel Performance Engineer - AI Accelerator

Amazon; Cupertino (CA); On-site; USD 193,000 - 262,000; Full time

Job summary

Amazon's Annapurna Labs seeks a Sr. ML Kernel Performance Engineer to advance AWS Neuron on Inferentia and Trainium. You will design high-performance kernels and optimize across generations, collaborating with compiler, runtime, framework, and hardware teams to push ML throughput.

This role offers exposure to cutting-edge AI acceleration and opportunities to mentor engineers while delivering production-grade kernel optimizations that scale with customer needs.

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language.
• 5+ years of leading design or architecture of new and existing systems.
• 5+ years of full software development life cycle, including coding standards and reviews.
• Experience as a mentor, tech lead or leading an engineering team.
• 6+ years of full software development experience.

Responsibilities

• Design and implement high-performance compute kernels for ML operations, leveraging the Neuron architecture and programming models.
• Analyze and optimize kernel-level performance across multiple generations of Neuron hardware.
• Conduct detailed performance analysis using profiling tools to identify bottlenecks.
• Implement compiler optimizations such as fusion, sharding, tiling, and scheduling.
• Work directly with customers to enable and optimize their ML models on AWS accelerators.
• Collaborate across teams to develop innovative kernel optimization techniques.

Skills

Kernel optimization

Performance analysis

Leadership/mentoring

ML acceleration

GPU architectures

Education

Bachelor's degree in computer science or equivalent

Tools

CUDA

NVIDIA PTX

Triton

OpenCL

SYCL

ROCm

Job description

Amazon's Annapurna Labs seeks a Sr. ML Kernel Performance Engineer to advance AWS Neuron on Inferentia and Trainium. You will design high-performance kernels and optimize across generations, collaborating with compiler, runtime, framework, and hardware teams to push ML throughput.

This role offers exposure to cutting-edge AI acceleration and opportunities to mentor engineers while delivering production-grade kernel optimizations that scale with customer needs.