OpenNash Jobs
Amazon · Austin, TX

Product Development Engineer, Annapurna Labs Silicon Operations

US, TX, AustinOperations

Listed on Amazon’s official careers site. Posted September 24, 2026. Check that it is still open and apply there.

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Job description

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

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