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.
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.
As a Thermal/Mechanical Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of AWS users.
In 2015, Annapurna Labs was acquired by Amazon Web Services (AWS). Since then, we have accelerated its innovation and developed a number of products that benefit cloud customers, including AWS Nitro technology, Inferentia custom Machine Learning chips, and AWS Graviton2 processors.
Annapurna Labs is a silicon/system and software organization that is delivering all the chips used by AWS customers. Today this includes: Graviton, driving innovation for general purpose compute; Nitro, driving networking and storage scale, security and Hypervisor offload, and Machine Learning (ML) Trainium and Inferentia that are enabling customers to train and run GenAI applications permanently while keeping costs under control.
Basic Qualifications:
Preferred Qualifications:
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .
USA, TX, Austin - 159,200.00 - 215,300.00 USD annually
USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually