Shape the future of AI infrastructure! Join AWS and develop system-level test solutions for our innovative ML acceleration hardware, deployed across our global server fleet.

Annapurna Labs (our organization within AWS) design hardware 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.

We're seeking highly skilled and motivated Product Test Engineers to join our Machine Learning Acceleration team at Annapurna Labs. In this role, you'll be at the forefront of validating and ensuring the quality of our advanced ML hardware systems as they transition from development to large-scale deployment across AWS's vast server fleet. You'll be responsible for designing and implementing comprehensive system-level test strategies that cover the full spectrum of our ML acceleration products, from individual components to fully integrated systems. This position requires a unique blend of hardware knowledge, software expertise, and systems thinking, as you'll be working at the intersection of custom silicon, complex firmware, and high-performance ML workloads.

You'll collaborate closely with cross-functional teams including hardware designers, software engineers, and operations specialists to develop robust test solutions that can scale to meet the demands of AWS's global infrastructure. Your work will be crucial in identifying and resolving integration issues, optimizing system performance, and ultimately ensuring that our ML acceleration products meet the highest standards of reliability and efficiency in real-world data center environments. If you're passionate about pushing the boundaries of ML hardware testing and have a knack for solving complex system-level challenges, we want you on our team.

Key job responsibilities
* Design and implement system-level test strategies for ML acceleration products
* Develop comprehensive functional and performance tests for complete ML systems
* Create and maintain scalable test infrastructure for high-volume product validation
* Implement product bring-up and first-boot test procedures
* Drive improvements in test coverage, product quality, and manufacturing efficiency
* Collaborate with hardware and software teams to ensure end-to-end product validation
* Analyze system-level test data to identify and resolve integration issues
* Debug complex hardware/software interactions in a production environment
* Develop and maintain documentation for system test procedures and manufacturing processes
* Optimize test workflows to balance thoroughness with production efficiency

A day in the life
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

About the team
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

*Diverse Experiences*
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

*Work/Life Balance*
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

*Inclusive Team Culture*
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

*Mentorship and Career Growth*
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional."

Product Test Engineer - Machine Learning Hardware, Annapurna Labs