The AWS Neuron Compiler team is actively seeking applied scientists to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI.

The Automated Reasoning Group in the AWS Neuron Compiler team works on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in compiler stack. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will contribute to the design and semantics of DSLs that our customers love when crafting neural architexctures. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role.

A background in machine learning and AI accelerators is preferred but not required. We expect a strong publication record in compilers, IR semantics, static analysis or verification.

A day in the life
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