Senior ML Kernel Performance Engineer

Amazon; Toronto; Hybrid; CAD 151,000 - 252,000; Full time

Benefits offered by this job

Health insurance

RRSP

DPSP

Paid time off

Job summary

Amazon's Annapurna Labs team is hiring engineers to design and optimize high-performance compute kernels for ML on Neuron. You will work across Neuron architecture generations, profiling and tuning for maximum throughput, and implement compiler optimizations while collaborating with customers to enable their models on AWS accelerators.

The role blends machine learning, high-performance computing, and distributed architectures in a startup-like environment, with mentorship and customer-facing

Qualifications

• 5+ years of full software development life cycle experience.
• Bachelor's degree in computer science or equivalent.
• Expertise in accelerator architectures for ML/HPC (GPUs/FPGA/ASIC).
• Experience with CUDA, OpenCL, ROCm and GPU backends.
• Proficiency with NVIDIA PTX and GPU ISA concepts.
• Experience developing high-performance HPC libraries.
• Strong low-level optimization for GPUs and ML frameworks.

Responsibilities

• Design and implement high-performance compute kernels for ML on Neuron.
• Optimize kernel performance across multiple Neuron generations.
• Perform detailed profiling to identify bottlenecks and improve throughput.
• Apply compiler optimizations: fusion, tiling, scheduling.
• Collaborate with customers to optimize models on AWS accelerators.
• Work cross-functionally to develop innovative kernel techniques.

Skills

SDLC experience

Accelerator architectures

GPU kernel optimization

NVIDIA PTX

High-performance libraries

GPU memory optimization

LLVM/MLIR backends

PyTorch / TensorFlow GPUs

Parallel programming

GPU backends knowledge

Education

Bachelor's degree

Tools

CUDA

OpenCL

ROCm

PyTorch

TensorFlow

LLVM

Job description

The Annapurna Labs team at Amazon builds Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon’s custom machine learning accelerators, Inferentia and Trainium.

The Acceleration Kernel Library team is at the forefront of maximizing performance for Amazon's custom ML accelerators. Working at the hardware-software boundary, our engineers craft high-performance kernels for ML functions, ensuring every FLOP counts in delivering optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.

The Amazon Neuron SDK, developed by the Annapurna Labs team at Amazon, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch, enabling unparalleled ML inference and training performance.

As part of the broader Neuron Compiler organization, our team works across multiple technology layers - from frameworks and compilers to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology.

This is an opportunity to work on cutting-edge products at the intersection of machine-learning, high-performance computing, and distributed architectures. You will architect and implement business-critical features, publish cutting-edge research, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We’re inventing. We’re experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on Amazon's ML accelerators.

Explore the product and our history!

https://awsdocs-neuron.readthedocs-hosted.com/en/latest/neuron-guide/neuron-cc/index.html

https://aws.amazon.com/machine-learning/neuron/

https://github.com/aws/aws-neuron-sdk

https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success

Key job 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 and resolve 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

A day in the life

As you design and code solutions to help our team drive efficiencies in software architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:

• Build high-impact solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business decisions with your technical input.
• Work in a startup-like development environment, where you’re always working on the most important stuff.

Qualifiche Preferenziali

• - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• - Bachelor's degree in computer science or equivalent
• • Expertise in accelerator architectures for ML or HPC such as GPUs, CPUs, FPGAs, or custom architectures
• • Experience with GPU kernel optimization and GPGPU computing such as CUDA, NKI, Triton, OpenCL, SYCL, or ROCm
• • Demonstrated experience with NVIDIA PTX and/or AMD GPU ISA
• • Experience developing high performance libraries for HPC applications
• • Proficiency in low-level performance optimization for GPUs
• • Experience with LLVM/MLIR backend development for GPUs
• • Knowledge of ML frameworks (PyTorch, TensorFlow) and their GPU backends
• • Experience with parallel programming and optimization techniques
• • Understanding of GPU memory hierarchies and optimization strategies

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSU). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, ON, Toronto - 150,700.00 - 251,700.00 CAD annually