[PhD] ML Compiler Engineer - Annapurna Labs, Annapurna Labs

Amazon

On-site 🏢 15 April
R&D, Innovation
Seattle, United States 🇺🇸 Cupertino, United States 🇺🇸

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 PhD Machine Learning Compiler Engineer 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, or Toronto.

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