Compiler Engineer, Neuron Automated Reasoning Group
Role Overview
Build the AWS Neuron compiler, which transforms machine-learning models from frameworks such as PyTorch, TensorFlow, and JAX for AWS Inferentia and Trainium servers.
Optimize compiler performance for varied workloads, including large language models, diffusion models, vision transformers, and multimodal models.
Key Skills for This Role
Full Job Posting
Role overview
Build the AWS Neuron compiler, which transforms machine-learning models from frameworks such as PyTorch, TensorFlow, and JAX for AWS Inferentia and Trainium servers.
Optimize compiler performance for varied workloads, including large language models, diffusion models, vision transformers, and multimodal models.
Responsibilities
- Design, implement, test, deploy, and maintain software that improves compiler performance, stability, and user experience.
- Create compiler optimization and verification passes, accelerator features, numerical-analysis tools, and defect fixes.
- Collaborate with chip architects, runtime and operating-system engineers, scientists, machine-learning application teams, and stakeholders.
- Help deploy customer machine-learning models on AWS accelerators with optimal cost and performance; contribute to pre-silicon design and product launches.
- Participate in design discussions, code reviews, and open-source work.
Basic qualifications
- At least 1 year of non-internship experience designing or architecting new and existing systems, including design patterns, reliability, and scaling.
- Experience programming in at least one software programming language.
Preferred qualifications
- Compiler experience or experience building machine-learning models with frameworks on accelerators such as GPUs is preferred, not required.
- OpenXLA, StableHLO, or MLIR experience is a bonus.
- Three or more years of full software development life-cycle experience is preferred.
- A bachelor's degree in computer science or equivalent is preferred.
Product and team
AWS Neuron is an SDK for optimizing machine-learning workloads on AWS Inferentia and Trainium custom chips.
The team supports knowledge-sharing, mentorship, and engineering career growth.
Compensation
- The posting lists annual starting pay of USD 129,000 for Seattle and USD 148,400 for Cupertino.
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