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资深硬件工程师 - 机器学习加速

雇主

Annapurna Labs (U.S.) Inc.

地点

Cupertino · 美国

待遇

$面议

工作模式

线下

截止日期

1月24日

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岗位摘要

Seeking a Senior Hardware Engineer to lead the design and validation of AWS next-generation ML chips

岗位职责

Annapurna Labs (our organization within Amazon) 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 outstanding and meaningful 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 centers.
You’ll provide leadership in the application of new technologies to large scale server deployments in a continuous effort to deliver a world-class customer experience.
This is a fast-paced, intellectually challenging position, and you’ll work with thought leaders in multiple technology areas.
You’ll have high standards for yourself and everyone you work with, and you’ll be constantly looking for ways to improve your products performance, quality and cost.
We’re changing an industry, and we want individuals who are ready for this challenge and want to reach beyond what is possible today.

申请条件

Proven experience in hardware design and validation, with a focus on PCIe and Serdes.
Experience with ML chips, cards, and server integration is highly desirable.
Demonstrated ability to lead technical projects and work effectively in a collaborative, fast-paced environment.

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数据来源:Amazon

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