Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training

Annapurna Labs (U.S.) Inc.; Cupertino (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. is seeking a Senior Machine Learning Engineer to join the AWS Neuron distributed training team. You will contribute to development, enablement, and performance tuning for large ML models, including GPT and other LLMs, on Trainium and Inferentia.

You'll work with chip architects, compilers, and runtime engineers to implement training support in PyTorch/JAX via XLA, and optimize for peak hardware efficiency.

Qualifications

• Bachelor's degree in computer science or equivalent
• 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
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing

Responsibilities

• Lead efforts to build distributed training support into PyTorch and JAX using XLA, the Neuron compiler, and runtime stacks.
• You will optimize models to achieve peak performance and maximize efficiency on AWS Trainium/Inferentia hardware.
• Collaborate with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions.

Skills

Python

Distributed training

PyTorch

JAX

Software development

System design

Education

Bachelor's degree in computer science or equivalent

Tools

XLA

Neuron compiler

Deepspeed

Nemo

PyTorch

JAX

Job description

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

AWS Neuron is the complete software stack for the AWS Trainium (Trn1/Trn2) and Inferentia (Inf1/Inf2) our cloud-scale Machine Learning accelerators. This role is for a Senior Machine Learning Engineer in the Distribute Training team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive-scale Large Language Models (LLM) such as GPT and Llama, as well as Stable Diffusion, Vision Transformers (ViT) and many more.

The ML Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with Trainium instances. Experience with training these large models using Python is a must. FSDP (Fully-Sharded Data Parallel), Deepspeed, Nemo and other distributed training libraries are central to this and extending all of this for the Neuron based system is key.

Key job responsibilities

You will lead efforts to build distributed training support into PyTorch and JAX using XLA, the Neuron compiler, and runtime stacks. You will optimize models to achieve peak performance and maximize efficiency on AWS custom silicon, including Trainium and Inferentia, as well as Trn2, Trn1, Inf1, and Inf2 servers. Strong software development skills, the ability to deep dive, work effectively within cross-functional teams, and a solid foundation in Machine Learning are critical for success in this role.

About the team

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.

About the team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

Diverse Experiences

AWS values diverse experiences. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences,

About AWS

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications:

• Bachelor's degree in computer science or equivalent
• 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
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing