Senior Architecture Modeling Engineer, AWS Machine Learning Accelerators

Custom SoCs (System on Chips) are the brains behind AWS’s Machine Learning servers. Our team builds C++ & SystemC functional models of these custom-designed accelerator SoCs for use by AWS internal teams. We’re looking for a Senior SoC Modeling Engineer to join the team and deliver new functional models, infrastructure, and tooling for our customers. As part of the ML accelerator modeling team, you will: - Develop and own SoC functional models end-to-end, including model architecture, integration with other model or infrastructure components, testing, and debug - Work closely with architecture, RTL design, design verification, emulation, and software teams to build, debug, and deploy your models - Innovate on the tooling you provide to customers, making it easier for them to use our SoC models - Drive model and modeling infrastructure performance improvements to help our models scale - Develop software which can be maintained, improved upon, documented, tested, and reused Annapurna Labs, our organization within AWS, designs and deploys some of the largest custom silicon in the world, with many subsystems that must all be modeled and tested with high quality. Our SoC model is a critical piece of software used in both our SoC development process and by our partner software teams. You’ll collaborate with many internal customers who depend on your models to be effective themselves, and you'll work closely with these teams to push the boundaries of how we're using modeling to build successful products. You will thrive in this role if you: - Are an expert in functional modeling for SoCs, ASICs, TPUs, GPUs, or CPUs - Are comfortable modeling in C++ or SystemC, and familiar with Python - Enjoy learning new technologies, building software at scale, moving fast, and working closely with colleagues as part of a small team within a large organization - Want to jump into an ML-aligned role, or get deeper into the details of ML at the hardware/system-level Although we are building machine learning chips, no machine learning background is needed for this role. This role spans modeling of the ML and management regions of our chips, and you’ll dip your toes into both. You’ll be able to ramp up on ML as part of this role, and any ML knowledge that’s required can be learned on-the-job. This role can be based in either Cupertino, CA or Austin, TX. The broader team is split between the two sites, with a slight preference for CA, due to colocation with more customer teams. 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! About the team AWS Utility Computing (UC) provides product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio. Annapurna Labs (our organization within AWS UC) 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. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the