Amazon

ML Kernel Performance Engineer, AWS Neuron, Annapurna Labs

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2 days ago
Cupertino, CA, USAMid Level
H1B Sponsor

Base Salary

$165k - $224k/yr

Responsibilities

  • Design and implement high-performance compute kernels for machine learning operations using the Neuron architecture and programming models.
  • Analyze and optimize kernel-level performance across multiple generations of Neuron hardware.
  • Use profiling tools to identify and resolve performance bottlenecks.
  • Implement compiler optimizations including fusion, sharding, tiling, and scheduling.
  • Work directly with customers to enable and optimize machine learning models on AWS accelerators.
  • Collaborate with compiler, runtime, framework, hardware, and other engineering teams on kernel optimization techniques.
  • Create metrics, implement automation, resolve software defects, participate in design discussions and code reviews, and communicate with stakeholders.

Requirements

  • At least 3 years of non-internship professional software development experience.
  • At least 2 years of non-internship experience designing or architecting new and existing systems, including design patterns, reliability, and scaling.
  • Experience programming with at least one software programming language.
  • Preferred: at least 3 years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
  • Preferred: bachelor's degree in computer science or equivalent.

Benefits

  • Comprehensive benefits including medical, dental, vision, prescription, life and AD&D insurance, employee assistance and mental health support, medical advice services, flexible spending accounts, and adoption and surrogacy reimbursement.
  • 401(k) matching, paid time off, and parental leave.
  • Sign-on payments and restricted stock units are included in the Amazon package.
  • The team offers flexibility in working hours and emphasizes work-life balance.
  • The position is located in Cupertino, California.

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