Amazon
Machine Learning - Compiler Engineer , AWS Neuron, Annapurna Labs
$144K–$224K
Seattle, WA +1 · Full-time · Posted Sep 17, 2026
- Location
- Seattle, WA
Cupertino, CA - Experience
- 3+ years of non-internship professional software development; 2+ years of non-internship design or architecture experience. Preferred: 3+ years writing production-grade code in object-oriented languages.
- Education
- Master's degree or PhD in Computer Science, or a related technical field (preferred).
About the job
Build and optimize the AWS Neuron compiler so machine-learning models run efficiently on AWS Inferentia and Trainium accelerators.
What you'll do
- Design, implement, test, deploy, and maintain compiler features, optimization and verification passes, and tools for analyzing numerical errors.
- Resolve compiler defects and improve performance, stability, and usability for a range of machine-learning workloads.
- Collaborate with chip architects, runtime and OS engineers, scientists, ML teams, and external stakeholders.
What they ask for
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship experience designing or architecting new and existing systems, including design patterns, reliability, and scaling.
- Experience programming with at least one software programming language.
Nice to have
- 3+ years writing production-grade code in object-oriented languages such as C++/Java.
- Experience in compiler design, open-source compiler toolsets, or technologies including OpenXLA, StableHLO, MLIR, PyTorch, JAX, TVM, Bazel, or CMake.
Pay
165,200.00 - 223,600.00 USD annually (base salary); 143,700.00 - 194,400.00 USD annually (base salary)
Tools
C++, Java, OpenXLA, StableHLO, MLIR, PyTorch, TensorFlow, JAX
AI focus
Develop compiler optimizations and tools for deploying and accelerating machine-learning models, including large language models, on AWS Inferentia and Trainium.
Model-written summary · the original posting is authoritative