Sr. Software Engineer- AI/ML, AWS Neuron

Amazon; Seattle (WA); On-site; USD 168,000 - 227,000; Full time

Job summary

Amazon in Seattle, WA seeks a Sr. Software Engineer – AI/ML for AWS Neuron to accelerate ML workloads on custom AI accelerators. You will design, optimize, and deploy high-performance ML models across multi-GPU and multi-node environments.

You will own performance tuning, work with open-source ecosystems, and collaborate with cross-functional teams to push the boundaries of AI acceleration for GenAI workloads.

Qualifications

• Bachelor's degree in a field related to software engineering.
• 5+ years of professional software development experience.
• Knowledge of Python and/or C++ programming.
• 5+ years of leading design or architecture of large-scale systems.
• Experience with debugging, profiling, and software engineering best practices.

Responsibilities

• Design, develop, and optimize ML models on custom AI accelerators.
• Participate in all stages of ML system lifecycle and distributed architectures.
• Build infrastructure to onboard multiple models with diverse architectures.
• Develop high-performance kernels for ML operations on Neuron hardware.
• Collaborate with customers to optimize their ML workloads on AWS accelerators.
• Lead optimization efforts and mentor engineers on performance.

Skills

Python

C++

Design/Architecture

Debugging/Profiling

Memory Management

Parallel Computing

PyTorch

NCCL

CUDA/Triton kernels

Education

Bachelor's degree

Master's degree (preferred)

Tools

PyTorch

CUDA

Triton

NCCL

Job description

Sr. Software Engineer – AI/ML, AWS Neuron

Shape the Future of AI Accelerators at AWS Neuron.

We build Amazon Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon’s custom machine learning accelerators, Inferentia and Trainium.

As a Senior Software Engineer on our Machine Learning Applications team, you will optimize the world's most demanding AI models at a scale few engineers ever get to work on. 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.

You can learn more about Neuron : https://awsdocs-neuron.readthedocs-hosted.com 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, develop, and optimize machine learning models including GPT, Kimi, and Qwen on custom AI accelerators.
• Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, low level optimizations, and production deployment.
• Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.
• Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models
• Analyze and optimize system-level performance across multiple generations of Neuron hardware
• Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks.
• Implement 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 optimization techniques.
• Develop kernels to improve model efficiency on Amazon AI Accelerators.
• Transform complex tensor operations into highly optimized graph implementations.
• Optimize state-of-the-art language, vision, and multimodal generative AI models for Neuron hardware.

What Makes This Role Unique

• Direct influence on AWS's AI Accelerator used by thousands of ML applications.
• Full-stack optimization from high-level frameworks to low level primitives.
• Collaboration with both open-source ML communities and hardware architecture teams.
• Requires passion for performance tuning and system architecture.

A day in the life

You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. 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 will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you’re always working on the most important initiative.

Work/Life Balance

Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.

About the team

At AWS Neuron, we're revolutionizing how the world's most sophisticated AI models run at scale through Amazon's next-generation AI accelerators. The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for Amazon's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic software stack, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers.

Basic Qualifications

• Bachelor's degree
• 5+ years of non-internship professional software development experience
• Knowledge of Python and/or C++ programming
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience in debugging, profiling, and implementing software engineering best practices in large-scale systems
• Knowledge of system performance, memory management, and parallel computing principles
• Experience owning a performance optimization roadmap and mentoring engineers on optimization

Preferred Qualifications

• Master's degree in computer science or equivalent
• Knowledge of machine learning model architecture and inference
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
• Hands-on development with PyTorch is preferred
• Experience scaling workloads across multi-GPU and multi-node topologies with NCCL and tensor, pipeline, or expert parallelism
• Experience writing and optimizing custom CUDA/Triton kernels for tensor operations

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.

USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

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