Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs

Join to apply for the Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs role at Amazon Web Services (AWS).

The AWS Neuron software stack includes an ML compiler, runtime and integrations into PyTorch, Tensor Flow and JAX. AWS Neuron is used at scale with customers such as Snap, Autodesk, Amazon Alexa and Rekognition, among others. The Neuron Compiler team develops a deep learning compiler stack that converts neural network descriptions created in frameworks into code for execution to push performance.

The Amazon Annapurna Labs team is responsible for silicon development at AWS, covering silicon engineering, hardware design and verification, software and operations.

As a Machine Learning Compiler Engineer II in 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 engineers excites and challenges you. You will work as a hands-on partner to AWS ML services teams and be involved in pre-silicon design, bringing new products/features to market, and 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 (perferred), Seattle, Austin.

Basic Qualifications

• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

• 2+ years of experience in developing compiler features and optimizations

• Proficiency with 1 or more of the following programming languages: C++ (preferred), C, Python

Preferred Qualifications

• Master or PhD degree in computer science or equivalent

• Proficiency with resource management, scheduling, code generation, and compute graph optimization

• Experience optimizing Tensorflow, PyTorch or JAX deep learning models

• Experience with multiple tool chains and Instruction Set Architectures

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.

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 you re applying in isn t listed, please contact your Recruiting Partner.

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  This position will remain posted until filled. Applicants should apply via our internal or external career site.

Company - Annapurna Labs (U.S.) Inc.

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