Annapurna Labs builds custom Machine Learning accelerators that are at the forefront of AWS innovation and one of several AWS tools used for building Generative AI on AWS. The Neuron Compiler team is searching for compiler-skilled engineering talent to support the development and scaling of a compiler to enable the world's largest ML workloads to run performantly on these custom Annapurna systems.

The Product: The AWS Machine Learning accelerators represent a pinnacle of AWS technologies, specifically designed for advancing AI capabilities. The Inferentia/Trainium chips specifically offer unparalleled ML inference and training performances. They are enabled through state-of-the-art software stack - the AWS Neuron Software Development Kit (SDK). This SDK comprises an ML compiler, runtime, and application framework, which seamlessly integrate into popular ML frameworks like PyTorch. AWS Neuron, running on Inferentia and Trainium, is trusted and used by leading customers such as Snap, Autodesk, and Amazon Alexa.

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.

Within this ecosystem, the Neuron Compiler team is developing a deep learning compiler stack that takes state of the art LLM and Vision models created in frameworks such as TensorFlow, PyTorch, and JAX, and makes them run performantly on our accelerators. The team is comprised of some of the brightest minds in the engineering, research, and product communities, focused on the ambitious goal of creating a toolchain that will provide a quantum leap in performance.

You: As a Sr. Machine Learning Compiler Engineer III on the AWS Neuron Compiler team, you will be supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads. Architecting and implementing business-critical features, publish cutting-edge research, and contributing to a brilliant team of experienced engineers excites and challenges you. You will leverage your technical communications skill as a hands-on partner to AWS ML services teams and you will be involved in pre-silicon design, bringing new products/features to market, and many other exciting projects.

A background in compiler development is strongly preferred. A background in Machine Learning and AI accelerators is preferred, but not required.

In order to be considered for this role, candidates must be currently located or willing to relocate to Cupertino (preferred), Seattle, Austin.

Key job responsibilities
Our engineers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base. You’ll bring a passion for innovation, data, search, analytics, and distributed systems. You’ll also:

Solve challenging technical problems, often ones not solved before, at every layer of the stack.
Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
Build high-quality, highly available, always-on products.
Research implementations that deliver the best possible experiences for customers.

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.

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. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

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.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices. Our hybrid models allow you the freedom to work from home whenever in-office collaboration isn’t necessary.- 6+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of experience in developing compiler features and optimizations
- Proficiency with 1 or more of the following programming languages: C++, C, Python- Masters degree or PhD in computer science or equivalent
- Experience optimizing Tensorflow, PyTorch or JAX deep learning models
- Experience with multiple toolchains like LLVM, OpenXLA/XLA, MLIR, TVM

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.