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

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Description

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 top ML inference performance at the lowest cloud cost. Trainium provides the highest ML training performance with extensive TFLOPS. This is enabled by the AWS Neuron SDK, which includes an ML compiler, runtime, and integration with frameworks like PyTorch, TensorFlow, and MxNet. AWS Neuron and Inferentia are utilized by clients such as Snap, Autodesk, Amazon Alexa, and Amazon Rekognition.

Team Overview

The Amazon Annapurna Labs team handles silicon development at AWS, covering silicon engineering, hardware design, and software. The AWS Neuron team focuses on optimizing neural net performance on AWS hardware, developing a deep learning compiler stack to convert neural network descriptions into executable code, aiming for significant performance improvements.

Your Role

As a Sr. Machine Learning Compiler Engineer III, you will support the development and scaling of a compiler for large ML workloads, architect and implement features, publish research, and mentor engineers. Your background in ML and AI accelerators is preferred but not required. Candidates must be willing to relocate to Cupertino, Seattle, Austin, or Toronto.

Additional Information

We prioritize inclusion, work-life balance, and career growth, offering flexible hours, mentorship, and development opportunities. The role offers a salary range based on geographic location, with additional benefits. The position remains open until filled. Apply via our career site.

Qualifications

• 5+ years of professional software development experience
• Proficiency in at least one programming language
• Experience in system design, architecture, and full SDLC
• Experience mentoring or leading teams

Preferred Qualifications

Amazon is an equal opportunity employer. For accommodations, visit https : / / amazon.jobs / content / en / how-we-hire / accommodations.

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