ML Compiler Engineer I, Annapurna Labs

Join Amazon as a Machine Learning Compiler Engineer I, Annapurna Labs. 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 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. 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. As a Machine Learning Compiler Engineer I 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. Responsibilities: Innovating and delivering creative SW Designs to develop new services, solve operational problems, drive improvements in developer velocity, or positively impact operational safety. Writing requirements capturing documents, design documents, integration test plans, and deployment plans. Communicating status and progress of deliverables to schedule, and sharing learnings/ innovations with your team and stakeholders. Basic Qualifications: To qualify, applicants should have earned (or will earn) a Bachelors or Masters degree between December 2022 and September 2025. Proficiency in C++ and Python programming, applied to compiler projects. Experience developing compiler optimizations or ML framework internals. Preferred Qualifications: Knowledge of code generation, compute graph optimization, resource scheduling. Experience optimizing Tensorflow, PyTorch or JAX deep learning models. Experience with multiple toolchains like LLVM, OpenXLA/XLA, MLIR, TVM. Familiarity with CUDA programming for GPU acceleration. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

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