Software Engineer-AI/ML, Inference Team - AWS Neuron
✨ AI Summary
Amazon is hiring a Software Engineer for the AWS Neuron team to build large-scale model inference serving technology on purpose-built accelerators. The role focuses on contributing to open-source frameworks like vLLM and SGLang, optimizing performance for continuous batching, paged attention, and distributed inference. The tech stack includes AWS Inferentia, Trainium, and Python-based ML frameworks. No specific years of experience or salary range are mentioned, but the team emphasizes mentorship and career growth in a Seattle-based role.
AWS Neuron is the complete software stack for AWS Inferentia and Trainium — AWS purpose-built accelerators for cloud-scale machine learning. Join the Machine Learning Inference Applications team to build the serving technology that lets customers run large-scale model inference fast and efficiently on Neuron chips.
As an engineer on this team, you'll work on core serving technologies within open-source frameworks such as vLLM and SGLang, optimizing model serving performance on Neuron and broadening the range of models we support out of the box. Your work directly accelerates how quickly new models are enabled, shipped, and delivered to customers.
Key job responsibilities
- Contribute core serving features to open-source inference frameworks such as vLLM and SGLang — implementing and upstreaming support for continuous batching, paged attention, quantization, and distributed inference on Neuron.
- Broaden the range of models supported out of the box, and build tooling and automation that shortens the path from a new model to a production-ready deployment.
- Improve model development and shipping velocity by reducing enablement time for new models and strengthening the test, benchmarking, and release workflows the team relies on.
- Collaborate with model development, performance, compiler, and runtime engineers to deliver end-to-end model performance — production-ready accuracy, scalability, and efficiency across a broad range of models and customer workloads.
- Apply strong engineering practices — code reviews, testing, and operational excellence — to ship reliable, high-performance inference that customers depend on.
About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.
About the Company
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