Custom silicon chips live at the heart of AWS machine learning servers (Trainium and Inferentia), and enable machine learning (ML) for AWS's customers. We’re looking for engineers to scale the system software team developing the hardware abstraction layer (HAL) that manages these cutting-edge ML system-on-chips (SoCs). The HAL forms the lowest level of the AWS infrastructure management software stack.
As a software engineer developing the SoC HAL, you will:
AWS's Annapurna Labs organization designs and deploys some of the largest custom silicon in the world, with many subsystems that must all be managed, tested, and monitored. The SoC HAL is a critical piece of the AWS infrastructure management software stack that ensure the chip is functional, performant, and secure.
You will thrive in this role if you:
Although we build and deploy ML chips, no ML background is needed for this role. You (and your software) won’t be doing ML. Our HAL lives at the lowest level of the backend AWS infrastructure responsible for managing our ML servers. You and your team will develop HALs for components used by machine learning, like PCIe and HBM, but won’t need to deeply understand ML yourselves.
This role can be based in either Cupertino, CA or Austin, TX. The team is split between the two sites, with no preference for one over the other.
This is a fast-paced role where 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 software, as well as our products' overall performance, quality, and cost.
We're changing an industry. We're searching for individuals who are ready for this challenge, who want to reach beyond what is possible today. Come join us and build the future of machine learning!
A day in the life
A few videos help explain what the Annapurna Labs ML team is working on:
About the team
Annapurna Labs, designs custom silicon powering AWS’s cloud infrastructure. Custom SoCs live at the heart of Amazon ML servers — including Inferentia and Trainium Systems — delivering high-performance ML inference and training at cloud scale.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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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, CA, Cupertino - 165,200.00 - 223,600.00 USD annually
USA, TX, Austin - 143,700.00 - 194,400.00 USD annually
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