This role is for a software engineer in the Compiler team for AWS Neuron. As part of this role, you will be responsible for building next generation Neuron compiler which transforms ML models written in ML frameworks (e.g, PyTorch, TensorFlow, and JAX) to be deployed AWS Inferentia and Trainium based servers in the Amazon cloud. You will be responsible for solving hard compiler optimization problems to achieve optimum performance for variety of ML model families including massive scale large language models like Llama, Deepseek, and beyond as well as stable diffusion, vision transformers and multi-model models. You will be required to understand how these models work inside-out to make informed decisions on how to best coax the compiler to generate optimal implementation instruction. You will leverage your technical communications skill to partner with internal and external customers/stakeholders and will be involved in pre-silicon design, bringing new products/features to market, ultimately, making Neuron compiler highly performant and easy-to-use.

You will design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler’s performance, stability and user-interface. You will work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy state of the art ML models from our customers on AWS accelerators with optimal cost/performance benefits. You will have opportunity to work with open-source software (e.g., StableHLO, OpenXLA, MLIR) to pioneer optimizing advanced ML workloads on AWS software and hardware. You will also work on building innovative features that will deliver best possible experiences for our customers – developers across the globe.