Annapurna Labs
Technology
ProductDevelopmentEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Product Development Engineer at Annapurna Labs. Skills: Silicon Yield, Product Engineering, Semiconductor Manufacturing, Data Analysis. Perform detailed data analysis. Optimize yield, test time”
What You'll Achieve.
Improve yield; Improve performance; Optimize test time; Implement optimal screening; Drive corrective actions; Improve quality
Industry & Context.
Analytical skills; Problem solving skills; Root cause analysis; Yield debug
What They're Looking For.
Must Have
Bachelor's degree in Electrical Engineering, 2+ years semiconductor industry experience, Experience using Python or scripting languages, Analytical and problem-solving skills
Nice to Have
Yield and performance optimization experience, Understanding of ATE test content, Experience setting test limits, Experience with power, performance characterization, Knowledge of ATPG scan diagnostics, Experience with SRAM bitmap analysis, Proficiency in statistical analysis tools, Automation for semiconductor test data, Experience building automated analysis systems, Experience building interactive dashboards, Familiarity with AWS services
What You'll Do.
Perform detailed data analysis
Implement optimal screening methodologies
Develop automation systems
Maintain automation systems
Compare yields across OSATs
Monitor performance metrics
Drive timely corrective actions
Lead functional test improvements
Lead structural test improvements
Perform targeted characterization
Collect critical performance data
Design comprehensive dashboards
Enable cross-functional teams
Automate alert systems
Identify issues rapidly
Resolve issues rapidly
Foster stakeholder relationships
Drive corrective actions
Collaborate with test engineering
Collaborate with system validation
Collaborate with DFT teams
How You'll Work.
Team & Collaboration
Cross-functional teams; Test engineering; System validation; DFT teams
Communication Scope
Stakeholder relationships
Process & Methodology
DOE planning
Full 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 identificatio
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