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

Amazon
Cupertino, CA, USA2026-05-27ONSITE

About the job

Do you want to be part of AI revolution? At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to cutting-edge infrastructure. In order to deliver on that vision, we’ve created innovative software and hardware solutions that make it possible. AWS Neuron is the SDK that optimizes the performance of complex ML models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads. This role is for a senior software engineer in the Compiler team for AWS Neuron.

Responsibilities

Design, implement, test, deploy and maintain innovative software solutions to transform Neuron compiler’s performance, stability and user-interface; Work side by side with chip architects, runtime/OS engineers, scientists and ML Apps teams to seamlessly deploy cutting edge ML models from our customers on AWS accelerators with optimal cost/performance benefits; Become front-face of Neuron Compiler to work with open-source communities (e.g., StableHLO, OpenXLA, MLIR) and influence industry wide partners to pioneer optimizing cutting-edge ML workloads on AWS software and hardware; Build innovative features that will deliver best possible experiences for our customers – developers across the globe.

Qualifications

Minimum

Bachelor's degree in computer science or equivalent; 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience; 3+ years of experience in developing compiler features and optimizations; Proficiency with 1 or more of the following programming languages: C++ (preferred), Python

Preferred

Master or PhD degree in computer science or equivalent; Proficiency with compiler design, resource management, instruction scheduling, memory allocation, data transfer optimization, compute graph optimization, code generation, and Instruction Set Architecture; Experience with LLVM and/or MLIR; Experience in LLM, Vision or other deep-learning models