Machine Learning - Compiler Engineer, Annapurna Labs

Overview

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

The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation and are used for building Generative AI on AWS. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium delivers best-in-class ML training performance with high TFLOPS for ML in the cloud. This is enabled by the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and native integration with popular ML frameworks such as PyTorch, TensorFlow and MXNet. AWS Neuron and Inferentia are used at scale with customers including Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more.

The Team: The Amazon Annapurna Labs team handles silicon development at AWS, covering silicon engineering, hardware design and verification, software and operations. The AWS Neuron team focuses on optimizing neural net models on our custom hardware, developing a deep learning compiler stack that translates network descriptions from frameworks like TensorFlow, PyTorch and MXNet into executable code. The team is composed of engineers, researchers and product professionals aiming to create a toolchain that will deliver a quantum leap in performance.

You: As a Machine Learning Compiler Engineer II on the AWS Neuron team, you will support ground-up development and scaling of a compiler to handle the world’s largest ML workloads. You will architect and implement business-critical features, publish cutting-edge research, and collaborate with experienced engineers. You will use your technical communication skills as a hands-on partner to AWS ML services teams, participate in pre-silicon design, help bring new products/features to market, and work on other exciting projects. A background in Machine Learning and AI accelerators is preferred, but not required.

Responsibilities

• Support the ground-up development and scaling of a compiler to handle large ML workloads.
• Architect and implement business-critical features.
• Publish cutting-edge research and contribute to a team of experienced engineers.
• Collaborate with AWS ML services teams; contribute to pre-silicon design; bring new products/features to market.

Basic Qualifications

• 3+ years of non-internship professional software development experience
• 2+ years of experience architecting and optimizing compilers
• Proficiency with one or more of the following languages: C++ (preferred), C, Python

Preferred Qualifications

• M.S. or Ph.D. in Computer Science or related field
• Experience with multiple toolchains and Instruction Set Architectures
• Proficiency with resource management, scheduling, code generation, and compute graph optimization
• Experience optimizing TensorFlow, PyTorch or MXNet deep learning models

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application and hiring 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 $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on factors including market location and job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be provided 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. | Job ID: A