Senior ML Kernel Performance Engineer

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

The Acceleration Kernel Library team is at the forefront of maximizing performance for Amazons 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 whats 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 Amazons 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 youll 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. Were inventing. Were 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 Amazons ML accelerators.

Explore the product and our history!
job responsibilities
Our kernel engineers collaborate across compiler runtime framework and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software hardware and machine learning systems youll bring expertise in low-level optimization system architecture and ML model this role you will:

* 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 youll create metrics implement automation and other improvements and resolve the root cause of software defects. Youll 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 youre always working on the most important stuff.

- 5 years of non-internship professional software development experience
- 5 years of programming with at least one software programming language experience
- 5 years of leading design or architecture (design patterns reliability and scaling) of new and existing systems experience
- Experience as a mentor tech lead or leading an engineering team

- 5 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Bachelors 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. As a total compensation company Amazons 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.

CAN ON Toronto - 150700.00 - 251700.00 CAD annually