Senior Product Development Engineer, Annapurna Labs Silicon Operations

Amazon is hiring a Senior Product Development Engineer, Annapurna Labs Silicon Operations in Austin, United States. It pays $185k-$250k a year and Level rates it ; you can apply on Level.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Sagemaker, Ate and semiconductor manufacturing.
Level files it as a senior role.
Level lists 22,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

Own end-to-end silicon yield and product engineering for advanced machine learning accelerator servers and chips.

sagemakerate

semiconductor-manufacturingyield-engineeringstatistical-analysismachine-learning-hardware

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.

Basic qualifications

- Bachelor's degree in Electrical Engineering or a related field
- 7+ years of semiconductor industry experience as a product/test engineer analyzing test data, including ownership of yield or test for a product at one or more insertions
- Experience using Python or other scripting languages for data analysis and automation
- Strong analytical and problem-solving skills
- Demonstrated ability to drive cross-functional initiatives and influence stakeholders without direct authority

Preferred qualifications

- Experience owning yield and performance optimization at system or ATE test on advanced FINFET nodes across a full product lifecycle
- Deep understanding of ATE test content (Scan, BIST, Functional, IO tests) and experience defining test limits and screening methodologies based on characterization
- Experience with power and performance characterization on high-performance chips
- Experience defining cost, schedule, and resource models for new product introduction (NPI)
- 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.
- Experience mentoring engineers and evaluating vendor tools/systems
- 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 - 185,200.00 - 250,000.00 USD annually

How we rate this

Senior Product Development Engineer, Annapurna Labs Silicon Operations at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Senior Product Development Engineer, Annapurna Labs Silicon Operations is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $185k-$250k a year.
The role is based in US, TX, Austin.
The job was posted on October 16, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Semiconductor ManufacturingYield EngineeringStatistical AnalysisMachine Learning HardwareSagemakerAte

Questions you could be asked

Tell me about a project where semiconductor manufacturing was part of your work. What did you do?
Tell me about a project where yield engineering was part of your work. What did you do?
Tell me about a project where statistical analysis was part of your work. What did you do?
Tell me about a project where machine learning hardware was part of your work. What did you do?
Walk me through how you've used Sagemaker in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Semiconductor Manufacturing, Yield Engineering, Statistical Analysis, Machine Learning Hardware, and Sagemaker. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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