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Hardware Engineer - ML Acceleration, Annapurna Labs
Amazon
📍
Cupertino, United States
Location
Cupertino
Posted
June 03, 2026
Commute
Local Area
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Job Description
Description
Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
We are seeking a Hardware Design Engineer with role in the definition, design and validation of AWS next generation ML Chips, Cards and server integration. As a senior member of our hardware team, you will have the opportunity to participate in the design and execution of all PCIe and Serdes topics, with the goal of creating and customized platforms that fit within AWS datacenter’s world leading technology.
As a member of the Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data cent...
Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
We are seeking a Hardware Design Engineer with role in the definition, design and validation of AWS next generation ML Chips, Cards and server integration. As a senior member of our hardware team, you will have the opportunity to participate in the design and execution of all PCIe and Serdes topics, with the goal of creating and customized platforms that fit within AWS datacenter’s world leading technology.
As a member of the Machine Learning Acceleration team you’ll be responsible for the design and optimization of hardware in our data cent...