Product Development Engineer

- Bachelor's degree in Electrical Engineering or a related field
- 2+ years of semiconductor industry experience as a product/test engineer analyzing test data
- Experience using Python or other scripting languages for data analysis and automation
- Strong analytical and problem-solving skills
- Experience with yield and performance optimization at system or ATE test on advanced FINFET nodes
- Understanding of ATE test content (Scan, BIST, Functional, IO tests) and experience setting test limits based on characterization.
- Experience with power, performance characterization on high performance chips.
- Knowledge of usage of ATPG scan diagnostics and SRAM bitmap analysis for FA and yield debug.
- Proficiency in statistical analysis tools (JMP, Python) and automation for semiconductor test data.
- Experience building automated analysis systems and interactive dashboards for yield and quality monitoring.
- Familiarity with AWS services (Sagemaker, S3, Quicksight etc.) and ability to use these for automation.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, TX, Austin - 153,600.00 - 215,000.00 USD annually
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.

We are seeking an experienced Silicon Yield Product engineer with expertise in yield debug on leading edge process technology nodes. This experienced engineer will be responsible for optimizing manufacturing process with foundry partners to improve yield and performance of our machine learning chips. They will interact with ATE, Systems test teams and Silicon design teams to identify systematic yield issues and work on debug to find root cause. This role involves 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.

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
- Perform detailed data analysis of ATE Test, SLT test, and System test data to optimize yield, test time, and implement optimal screening methodologies across platforms.
- Develop and maintain automation systems to compare yields across OSATs, testers, and setups, while monitoring performance metrics to drive timely corrective actions.
- Lead functional and structural test coverage improvements at ATE and system levels through strategic DOE planning and targeted characterization efforts to collect critical performance data.
- Design and maintain comprehensive dashboards enabling cross-functional teams to monitor key metrics, with automated alert systems for rapid issue identification and resolution.
- Foster strong stakeholder relationships and drive corrective actions for yield and quality improvements through effective collaboration with test engineering, system validation, and DFT teams