Software Dev Engineer Intern - Machine Learning Chip Architect

Amazon

On-site 🏢 03 October
Data Science & AI/ML
Cupertino, United States 🇺🇸

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.We are on the lookout for the curious, those who think big and want to define the world of tomorrow. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.Are you a student interested in computer architecture, machine learning, performance optimization, or application-specific silicon design? We are looking for engineers capable of using a variety of domain expertise to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment.Key job responsibilitiesAs a member of the ML chip architecture team, you will be responsible for accelerating large-scale machine learning workloads holistically across algorithms, software, and hardware, as part of our continuous effort to deliver a world-class customer experience. You will be the interface between SW and HW teams, bridging the gap between silicon capabilities and application requirements. Finally, you will have a chance to drive performance improvements on existing AWS hardware platforms, as well as propose, evaluate, and develop hardware optimizations targeting future generations of our products.If this sounds exciting to you - come build the future with us!Internal job descriptionThis requisition is for external candidates or campus employee referrals only, and is not eligible for internal transfers.Due to the volume of referrals and external applicants received, ECT team is unable to provide status updates on individual applicants. Please help us in setting expectations with our candidates and encourage them to reference their application portal for the most up to date information on their application.

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