# Software Development Engineer I, Inference models optimization, AWS Neuron Inference at Amazon

Amazon is hiring a Software Development Engineer I, Inference models optimization, AWS Neuron Inference in Cupertino, United States. It pays $127k-$185k a year and Level rates it Builds AI ●●●●; you can [apply on Amazon](https://jobsbylevel.com/go/e6728cfa-47ee-4277-b112-2113db6ff407?utm_medium=ai-agent).

AI Level 4, AI centrality 92 out of 100. US, CA, Cupertino.

## Details

- Company: [Amazon](https://jobsbylevel.com/companies/amazon)
- AI level: AI Level 4 (score 92 out of 100)
- Location: US, CA, Cupertino
- Salary: $127k-$185k
- Posted: November 10, 2026
- Apply: https://jobsbylevel.com/go/e6728cfa-47ee-4277-b112-2113db6ff407?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=software-development-engineer-i-inference-models-optimization-aws-neuron-inference-at-amazon-954eaa

## Prepare for this job

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## Description

The Annapurna Labs team at Amazon Web Services (AWS) builds the AWS Neuron SDK, the software development kit used to accelerate deep learning and GenAI workloads on AWS Trainium machine learning accelerators. The Neuron Inference organization is at the forefront of optimizing inference performance for a wide range of ML models and model architectures on AWS's custom ML accelerators. We are working across the stack from PyTorch to the hardware-software boundary, our engineers build systematic infrastructure, develop high-performance kernels for ML functions, ensuring every compute unit is fine-tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. As part of the broader Neuron organization, our team works across multiple technology layers — from frameworks and kernels through to compiler, runtime, and collectives. We not only optimize performance on open weight models but also contribute to future architecture designs and work closely with customers to enable optimal performance on their models. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology. As a Software Engineer I, you will design and implement business-critical features and contribute to optimizing the performance of models on AWS Trainium end to end. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team also collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers. This role is responsible for development, enablement, and performance tuning of a wide variety of LLM model families, including massive-scale large language models like GLM, Kimi, and beyond. The Model Enablement team works side by side with compiler engineers and runtime engineers to create, build, and tune distributed inference solutions with AWS Trainium. You can learn more about Neuron: * https://awsdocs-neuron.readthedocs-hosted.com/en/latest/compiler/index.html * https://aws.amazon.com/machine-learning/neuron/ * https://github.com/aws/aws-neuron-sdk * https://github.com/vllm-project/vllm-neuron * https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success If this sounds exciting to you - come build the future with us! Key job responsibilities * Optimize open models to run best on Trainium, including optimizing sharding, developing NKI kernels and ensuring accuracy. This provides ready-to-serve models to our customers and also gives them a starting point to optimize their own. * Collaborate with cross-disciplinary teams that may include hardware design, firmware, compiler, runtime, and ML engineers to develop software that enables and optimizes custom ML accelerator silicon * Write clean, maintainable code (C/C++, Python, or Rust) following best practices for systems-level and performance-critical development * Participate in code reviews, contribute to technical documentation, and help deploy agentic tools to accelerate the enablement of new models on Trainium * Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities * Keep learning emerging technologies in ML accelerators, compiler optimization, computer architecture, and cloud-scale distributed systems About the team The Model Enablement team fosters a builder's culture where experimentation is

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