System Development Engineer (Bengaluru)

System Development Engineer (Bengaluru)

09 Oct
|
Amazon
|
Bengaluru

09 Oct

Amazon

Bengaluru

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 Amazon's 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.

Basic Qualifications:
- Bachelor's degree or above in computer science, computer engineering, or related field
- Experience working in a Linux/Unix environment
- Robust 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

Preferred Qualifications:
- Familiarity with machine learning fundamentals — model formats, quantization, inference vs training
- Expe

📌 System Development Engineer (Bengaluru)
🏢 Amazon
📍 Bengaluru

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