Product Development Engineer, Annapurna Labs Silicon Operations

Amazon

Austin (TX)

On-site

USD 136,000 - 184,000

Full time

14 days+
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Benefits offered by this job

Health insurance
RSUs
401(k) matching
Paid time off

Job summary

Amazon, through its AWS Annapurna team, seeks a Silicon Yield Product Engineer in Austin, TX to optimize yield for next-generation machine learning silicon. You will work with ATE, systems test, and silicon design teams to identify root causes and implement robust screening and monitoring solutions.

The role emphasizes data-driven yield improvements, development of automated dashboards, and close collaboration with test engineering, validation, and DFT teams.

Qualifications

  • Bachelor's degree in Electrical Engineering or 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.

Responsibilities

  • Perform detailed data analysis of ATE Test, SLT test, and System test data to optimize yield and test time.
  • Develop and maintain automation systems to compare yields across OSATs, testers, and setups.
  • Lead functional and structural test coverage improvements at ATE and system levels through DOE planning and characterization.
  • Design dashboards enabling cross-functional teams to monitor key metrics with automated alerts.
  • Foster stakeholder relationships and drive corrective actions for yield and quality.

Skills

Python scripting
Data analysis
Electrical engineering background
Analytical thinking

Education

Bachelor's degree in Electrical Engineering

Tools

JMP
ATPG scan diagnostics
SRAM bitmap analysis

Job description

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
About the team
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.

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.

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.

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.

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.

Basic Qualifications
  • 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
Preferred Qualifications
  • 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 - 136,000.00 - 184,000.00 USD annually

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