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Silicon Yield and Test Data Analysis Engineer, Annapurna Silicon Operations
Amazon
Operations, Data Science
Austin, TX, USA
Posted on Dec 24, 2024
DESCRIPTION
We are seeking an experienced Silicon Yield Data Analysis Engineer with expertise in silicon test data analysis, automation and yield debug.
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 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-Annapurna team develops the silicon used in our most advanced machine learning accelerator servers at cutting edge process nodes. These SOCs are used in massively scaled server clusters to provide best hardware platform for our customers to run training and inference workloads.
Our final product is a server, not just the silicon, so you will find yourself stretching beyond traditional silicon product engineering boundaries and dealing with various system issues and data sets, providing ample opportunities to learn.
Key job responsibilities
This experienced engineer will be responsible for:
- Building our data systems which parse data from various ATE and system level test platforms and generating analysis which provide actionable information impacting key product metrics like yield, performance and test cost.
- Developing analysis dashboards that are widely used across the organization and implementing early warning alert systems to warn the test owners about manufacturing excursions.
- Interacting with ATE, Systems test teams and Silicon design teams to identify systematic manufacturing issues and work with other product engineers to debug and root cause.
- Collaborating with various teams to develop innovative solutions to optimize yield and performance for our products. Strong analytical and problem solving skills, knowledge of semiconductor manufacturing process and expertise in statistical analysis are essential for success in this role.
About the team
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 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 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 & 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.
BASIC QUALIFICATIONS
- Bachelors or Masters in Electrical or Computer engineering
- 5+ years of experience working on semiconductor test data analysis and automation
- 3+ years of experience conducting data analysis of foundry WAT data, ATE test data and/or system level test data using tools like JMP, Python etc.
PREFERRED QUALIFICATIONS
- Experience working on yield and power/performance characterization datasets of digital semiconductor chips.
- Basic understanding of fab process flow for leading technology nodes and ability to drive corrective actions based on ATE test data, WAT data and system test data analysis
- Experience building dashboards and automated analysis scripts
- Experience building data analytics systems with AWS tools like S3, Sagemaker and Quicksight
- Proficiency in test data analysis and statistics using tools like JMP and Python.
- Basic understanding of ATE test content to drive debug for SCAN ATPG and SRAM yield issues.
- Experience driving corrective actions across cross-functional teams to fix and root-cause systematic yield issues and improve product yield and cost.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.