Sr. Hardware Engineer - ML Acceleration, Annapurna Labs

Amazon; Austin (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

Amazon seeks a Hardware Design Engineer to define and validate next-gen ML Chips and server integration as part of the Machine Learning Acceleration team. The role encompasses hardware design and optimization in AWS data centers, focusing on enhancing product performance and quality, while fostering an inclusive culture within a fast-paced environment.

Qualifications

• Experience in developing functional specifications and verification plans.
• Master’s degree in electrical engineering or computer engineering.
• Experience managing technical projects.

Responsibilities

• Define, design, and validate next-generation ML Chips.
• Lead application of new technologies for large-scale server deployments.

Skills

Design verification

Project management

Education

Master’s degree in electrical engineering

Job description

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to new product innovations that set AWS’s services apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers requiring specialized security solutions.

Annapurna Labs, within AWS UC, designs silicon and software that accelerate innovation. Customers choose us to create cloud solutions that solve unprecedented challenges. Our custom chips, accelerators, and software stacks enable us to tackle technical challenges never seen before, delivering results that help our customers change the world.

We are seeking a Hardware Design Engineer to define, design, and validate AWS’s next-generation ML Chips, Cards, and server integration. As a senior hardware team member, you will participate in designing and executing PCIe and Serdes topics, creating customized platforms for AWS data centers.

As part of the Machine Learning Acceleration team, you’ll be responsible for hardware design and optimization in our data centers. You’ll lead the application of new technologies to large-scale server deployments, continuously enhancing customer experience. This fast-paced, challenging role involves working with thought leaders across technology areas, with a focus on improving product performance, quality, and cost. We’re changing the industry, and we seek individuals eager to push beyond current limits.

About the team

Why AWS

Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, pioneering cloud computing with ongoing innovation. Customers from startups to Global 500 companies trust our robust suite of products and services.

Utility Computing (UC)

AWS UC provides product innovations, from foundational services like S3 and EC2 to new innovations that distinguish AWS in the industry. As a UC team member, you’ll support the development and management of Compute, Database, Storage, IoT, Platform, and Productivity services, including security solutions for cloud customers.

Inclusive Team Culture

At AWS, learning and curiosity are core values. Our employee-led affinity groups foster inclusion, empowering us to celebrate our differences. Events like CORE and AmazeCon promote diversity and continuous learning.

Work/Life Balance

We value work-life harmony and offer flexibility to support your success at work and at home. A supported work environment enables us to achieve more together.

Mentorship and Career Growth

We aim to be Earth’s Best Employer by providing knowledge-sharing, mentorship, and career development resources to help you grow professionally.

Diverse Experiences

We encourage candidates from all backgrounds to apply, even if you do not meet every qualification. Diverse experiences enrich our team and innovation.

Minimum Qualifications

• Experience in developing functional specifications, design verification plans, and test procedures
• Master’s degree in electrical engineering, computer engineering, or equivalent
• Experience working with interdisciplinary teams from concept to production
• Experience managing technical projects

Amazon is an equal opportunity employer. For workplace accommodations during the application process, visit this link.