Software Development Engineer Intern - Machine Learning Chip Architect, Annapurna Labs

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 seeking the curious, those who think big and wish to shape the world of tomorrow. At Amazon, you will mature into the influential, forward-thinking individual you know you are ready to be. Every day will be filled with stimulating new challenges, developing new skills, and achieving personal growth. How often can you say that your work impacts the world? At Amazon, you'll say it often. Join us and shape tomorrow. Are you a student interested in computer architecture, machine learning, performance optimization, or application-specific silicon design? We are looking for engineers who can utilise a mixture of domain expertise to invent, design, promote, and implement cutting-edge solutions for unprecedented problems. A successful candidate will be proactive, comfortable with uncertainty, have strong attention to detail and ability to work in a fast-paced, ever-evolving environment. Key job responsibilities As part of the ML chip architecture team, you will be accountable for accelerating large-scale machine learning assignments across algorithms, software, and hardware, as part of our ongoing effort to provide a top-notch customer experience. You will be the intermediary between software and hardware teams, closing the gap between silicon capabilities and application requirements. Lastly, you will have the opportunity to enhance performance on existing AWS hardware platforms, and propose, assess, and develop hardware improvements targeting future product generations. If this sounds exhilarating to you - join us and build the future! This job post is for external candidates or campus employee referrals only; it is ineligible for internal transfers. Due to the large number of referrals and external applicants, our team cannot provide individual application updates. Please request that candidates reference their application portal for the latest information on their application. We are open to hiring candidates to work in any of the following locations: Cupertino, CA, USA Basic Qualifications • Working towards a Bachelor's degree or higher in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, or related fields, with an expected graduation date between December 2024 and September 2026. • Knowledge or previous experience in computer architecture and silicon design. • Experience with C++, Rust, or other programming languages, as well as Python, or a similar scripting language. Preferred Qualifications • Familiarity or experience with machine learning applications and performance tuning on accelerators such as GPUs, TPUs, or the like. • Familiarity or experience with RTL coding using Verilog, SystemVerilog, or a similar language. • Outstanding critical thinking skills, coupled with the ability to convey your arguments clearly and compellingly in both spoken and written form. • Technical fluency; comfort in understanding and discussing architectural concepts and algorithms, schedule tradeoffs, and new opportunities with technical team members. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate by race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who wish to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects labor costs across several US geographic markets. The base pay for this position ranges from $42.50/hr in our lowest geographic market up to $96.15/hr in our highest geographic market. Pay is based on factors such as market location and can vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other compensation forms may be included in a total compensation package alongside a complete range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.