AWS-Annapurna Labs 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 the best hardware platform for our customers to run training and inference workloads.
We are seeking a Senior Silicon Yield Product Engineer to take full ownership of a product's yield across one or more test insertions — from wafer sort through package final test, system level test, and downstream card/server/fleet test.
You will set the yield strategy for your product by identifying and prioritizing the cost and quality activities, aligning requirements with key stakeholders, and directing the work of other engineers to deliver against them.
You will engage foundry, OSAT, DFT, supply chain, test, manufacturing, and system validation partners at a strategic level to define the cost, schedule, and resource models required to bring a new product to production.
Because our final product is a server, not just the silicon, you will routinely stretch beyond traditional silicon product engineering boundaries — solving complex, cross-organizational problems that no single team owns.
Strong analytical and problem-solving skills, deep knowledge of semiconductor manufacturing processes, and expertise in statistical analysis are essential.
Key job responsibilities
- Own the end-to-end yield of one or more products across wafer sort, final test, SLT, driving both systematic yield improvement and excursion response to targets you help define.
- Identify and address customer quality issues by monitoring downstream yields and quality from card test through customer utilization in production.
- Identify and prioritize cost, quality, characterization activities, and assign and coordinate the work across a team of engineers.
- Align product requirements with key stakeholders, and define and drive the cost, schedule, and resource requirements to successfully deliver a new product to production.
- Create new tools and analysis flows to keep pace with the rising complexity of Machine Learning products, and evaluate new tools and systems offered by external vendors.
- Engage strategically with DFT, supply chain, test, manufacturing, quality, foundry, and
OSAT teams as a trusted resource counted on to solve complex problems requiring cross-organizational expertise.
- Lead functional and structural test coverage improvements at ATE and system through DOE planning and targeted characterization.
- Mentor junior engineers, identify knowledge and skill gaps within the team, and define growth paths for individuals and the organization.