Are you passionate about running large AI models directly on consumer devices where every millisecond milliwatt and megabyte matters Join our team to work at the core of the Neural Network Accelerator (NNA) software stack driving on-device machine-learning inference compiler and runtime development and the automation infrastructure that ships production-quality AI features to millions of Amazon devices.

Key job responsibilities
As a SysDE I on the NNA / EdgeAI team you will contribute to the software stack that compiles deploys and runs vision and language models on Amazons in-house neural accelerators. You will work across the ML compilation pipeline (quantization graph lowering kernel selection artifact packaging) the on-device inference runtime (secure and non-secure execution paths memory and bandwidth budgets) and the release and validation infrastructure that keeps our device fleet healthy build over build.

A day in the life
You will help build and improve the test and evaluation systems that validate model accuracy latency memory footprint and stability on physical devices in the lab including large-scale evaluation of Vision-Language Models (VLMs) end-to-end from reference to device. You will also contribute to the build release and CI automation that keeps our multi-package software stack shipping cleanly across product platforms.

This role sits at the intersection of ML systems embedded software and release engineering.





- Bachelors degree or above in computer science computer engineering or related field
- Experience working in a Linux/Unix environment
- Solid programming skills in one or more of C C Python
- Experience with automating building testing or deploying software
- Experience with CI/CD pipelines build systems and multi-package release engineering

- Familiarity with machine learning fundamentals model formats quantization inference vs training
- Experience with on-device or embedded ML runtimes ML compilers or accelerator toolchains
- Experience with device-side debugging: kernel logs driver logs ADB on-device tracing
- Familiarity with cloud infrastructure (AWS) for large-scale test execution log storage and metrics
- Familiarity with agent-based / AI-assisted developer tooling for triage code review or release automation
- Minimum 3 year of experience in ML systems embedded software or release engineering

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Required Experience:

IC

📌 System Development Engineer EdgeAI, HW Compute Group (Bengaluru)
🏢 Amazon
📍 Bengaluru