The candidate must be currently enrolled in a Bachelor's or Master's degree program in Electrical Engineering, Computer Engineering, or a related field. They should have a strong understanding of VLSI circuit design and have completed relevant coursework and lab projects. Additionally, experience with scripting languages such as Python or Perl, as well as knowledge of FinFET design, EDA tools, and Verilog/SystemVerilog, is preferred.

The candidate will be responsible for performing physical design, including chip floorplanning, analysis, optimization, script writing, and collaboration with designers, for Amazon's machine learning custom silicon solutions.

Engineering

United States

Austin

Large

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. We are driven by the excitement of building technologies, inventing products, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope and capabilities of a large company, and the spirit and heart of a small one.

Together, Amazonians research and develop new technologies from Amazon Web Services to Alexa on behalf of our customers: shoppers, sellers, content creators, and developers around the world.

Our mission is to be Earth's most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind.

You'll also hear us say that at Amazon, it's always "Day 1."​ What do we mean? That our approach remains the same as it was on Amazon's very first day - to make smart, fast decisions, stay nimble, invent, and focus on delighting our customers.

Retail & Consumer Goods

Amazon

Technology

<ul><li>Amazon Web Services (AWS) internships are&nbsp;full-time&nbsp;(40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.</li><li>In Annapurna Labs we are at the forefront of hardware co-design not just in Amazon Web Services (AWS) but across the industry. The work we do is cutting-edge and internet-scale while also being deeply important to our customers. We design and build every component of our hardware and software to come together into products that our customers use for accelerated computing: either Machine Learning acceleration, or FPGA acceleration. We get our hands dirty, from creating our own silicon, pushing the electrons in the right direction, ensuring our hardware is functional and healthy, and managing the full lifecycle of our systems at the huge scale and complexity of AWS. If you're interested in "building a complete product" from inception to delighted customers, Annapurna is a fantastic choice.</li><li>As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of Software and Hardware in our data centers including technologies such as AWS Inferentia, which is a machine learning inference accelerator designed to deliver high performance at low cost.</li><li>If this sounds exciting to you - come build the future with us!</li></ul>

Currently Studying

Bachelors

Masters

Amazon Web Services (AWS) internships are full-time (40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.In Annapurna Labs we are at the forefront of hardware co-design not just in Amazon Web Services (AWS) but across the industry. The work we do is cutting-edge and internet-scale while also being deeply important to our customers. We design and build every component of our hardware and software to come together into products that our customers use for accelerated computing: either Machine Learning acceleration, or FPGA acceleration. We get our hands dirty, from creating our own silicon, pushing the electrons in the right direction, ensuring our hardware is functional and healthy, and managing the full lifecycle of our systems at the huge scale and complexity of AWS. If you're interested in "building a complete product" from inception to delighted customers, Annapurna is a fantastic choice.As a member of the Cloud-Scale Machine Learning Acceleration team you’ll be responsible for the design and optimization of Software and Hardware in our data centers including technologies such as AWS Inferentia, which is a machine learning inference accelerator designed to deliver high performance at low cost.If this sounds exciting to you - come build the future with us!

2024 ASIC Physical Design Engineer Intern, Annapurna Labs

Requirements

Responsibilities

Amazon

Mission & Purpose