Description

The Product: Amazon's Machine Learning accelerators are at the forefront of our innovation and one of several Amazon's tools used for building Generative AI on Amazon. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by cutting edge software stack, the Amazon Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. Amazon Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition and more customers in various other segments.

The Team: As a whole, the Amazon Annapurna Labs team is responsible for silicon development at Amazon. The team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations.

The Amazon Neuron team works to optimize the performance of complex neural net models on our custom-built Amazon hardware. More specifically, the AWS Neuron team is developing a deep learning compiler stack that takes neural network descriptions created in frameworks such as TensorFlow, PyTorch, and MXNET, and converts them into code suitable for execution. As you might expect, 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: Machine Learning Compiler Engineer on the Amazon Neuron 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 Machine Learning and AI accelerators is preferred, but not required.