AWS Utility Computing (UC) is at the forefront of cloud innovation, particularly through Annapurna Labs, which designs cutting-edge silicon and software solutions. This role focuses on developing physical design methodologies for ML Accelerator chips, including AWS Inferentia and Trainium Systems. As a Sr. Physical Design Methodology Engineer, you'll be crucial in creating and optimizing hardware designs for AWS's machine learning infrastructure.
The position combines deep technical expertise in ASIC design with the excitement of working on next-generation cloud computing and AI technologies. You'll be part of a team that values knowledge-sharing, mentorship, and continuous learning, while working on projects that directly impact AWS's cloud computing capabilities.
The role offers competitive compensation ($143,300-$247,600 based on location), comprehensive benefits, and the opportunity to work with world-class engineers. AWS's inclusive culture, commitment to work-life harmony, and focus on career development make this an ideal position for experienced engineers looking to make a significant impact in cloud computing and machine learning infrastructure.
Working at AWS means joining a company that powers hundreds of thousands of businesses across 190 countries, with data centers globally. The role provides exposure to cutting-edge technologies, including AWS's growing suite of generative AI services, while working on solutions that help customers tackle previously impossible challenges.