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 consistently released new 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, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. 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. AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn1 and Inf1 servers that use them. This role is for a senior software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale large language models like GPT2, GPT3 and beyond, as well as stable diffusion, Vision Transformers and many more. The ML Apps team works side by side with chip architects, compiler engineers and runtime engineers to create , build and tune distributed training solutions with Trn1. Experience training these large models using Python is a must. FSDP, Deepspeed and other distributed training libraries are central to this and extending all of this for the Neuron based system is key. Key job responsibilities Design-for-Test (DFT) is a multi-disciplinary field of growing complexity that involves close cooperation and mutual work with multiple VLSI engineering groups, including architecture, frontend design, verification, physical implementation, signal integrity, test, reliability and more. DFT engineers participate in the whole chip design process from start to end, defining our future products, implementing them and debugging real devices in Amazon fleet. They hold a lot of responsibility and are a major part of our success. In this role you will be part of the chip design group, working on: Development and implementation of DFT architecture Design and verification of DFT logic and components Generation of high-quality test and debug patterns Static timing analysis of DFT modes Silicon bring-up, diagnosis and support for physical failure analysis A day in the life Annapurna Labs is a fabless semiconductor company established by semiconductor industry veterans and is part of Amazon Web Services (AWS). We are developing leading edge products widely used in the Amazon cloud. Annapurna Labs is like a big start-up in AWS. We develop using cutting-edge technologies, work with amazingly talented engineers, innovate and truly shape the future. Working for Annapurna Labs is thrilling, fast-paced, and a constant learning experience. Our offices are located in Sarona/Tel Aviv and Matam/Haifa. One of our main products is the Graviton ARM based server. If you are interested in hearing more, you are welcome to watch the following videos: Graviton3 presented during AWS re:Invent conference: AWS re:Invent 2021 – Keynote with Peter DeSantis (around minute 37) https://www.youtube.com/watch?v=9NEQbFLtDmg There is also in depth session about AWS Graviton: AWS re:Invent 2022 - AWS Graviton deep dive: The best price performance for AWS workloads https://www.youtube.com/watch?v=lZkO-KelLnk And all about AWS building its own chips (these are the products done by Annapurna Labs team): AWS re:Invent 2022 - Silicon innovation at AWS https://www.youtube.com/watch?v=O6EMdeuq\_s8 About the team About AWS Diverse Experiences AWS 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. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & 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. 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. Basic Qualifications - BSc degree in Computer/Electrical Engineering from leading universities. - 3+ years of experience in Chip Design/ DFT/ Design Verification Preferred Qualifications - Verilog, System Verilog - UVM methodology - Scripting skills Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.