What are the responsibilities and job description for the 2025 Product Development Engineer Intern, Annapurna Labs position at Lensa?
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Description
Amazon Web Services (AWS) internships are full-time (40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.
In Annapurna Labs we are at the forefront of hardware co-design not just in Amazon Web Services (AWS) but across the industry. The work we do is cutting-edge and internet-scale while also being deeply important to our customers. We design and build every component of our hardware and software to come together into products that our customers use for accelerated computing: either Machine Learning acceleration, or FPGA acceleration. We get our hands dirty, from creating our own silicon, pushing the electrons in the right direction, ensuring our hardware is functional and healthy, and managing the full lifecycle of our systems at the huge scale and complexity of AWS. If you're interested in "building a complete product" from inception to delighted customers, Annapurna is a fantastic choice.
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. Machine learning operations product development engineering team focuses on optimizing key manufacturing metrics like yield, test cost and test coverage for our products across ATE test and System test insertions. We are also responsible for thorough power/performance characterization of our newest silicon with a goal of optimizing system power/performance with adaptive scaling schemes and improving foundry process.
Our final product is a server, not just the silicon, so you will find yourself stretching beyond traditional silicon product engineering boundaries working to resolve both silicon and system related manufacturing issues, providing ample opportunities to learn.
Key job responsibilities
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.
Description
Amazon Web Services (AWS) internships are full-time (40 hours/week) for 12 consecutive weeks during summer. By applying to this position, your application will be considered for all locations we hire for in the United States.
In Annapurna Labs we are at the forefront of hardware co-design not just in Amazon Web Services (AWS) but across the industry. The work we do is cutting-edge and internet-scale while also being deeply important to our customers. We design and build every component of our hardware and software to come together into products that our customers use for accelerated computing: either Machine Learning acceleration, or FPGA acceleration. We get our hands dirty, from creating our own silicon, pushing the electrons in the right direction, ensuring our hardware is functional and healthy, and managing the full lifecycle of our systems at the huge scale and complexity of AWS. If you're interested in "building a complete product" from inception to delighted customers, Annapurna is a fantastic choice.
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. Machine learning operations product development engineering team focuses on optimizing key manufacturing metrics like yield, test cost and test coverage for our products across ATE test and System test insertions. We are also responsible for thorough power/performance characterization of our newest silicon with a goal of optimizing system power/performance with adaptive scaling schemes and improving foundry process.
Our final product is a server, not just the silicon, so you will find yourself stretching beyond traditional silicon product engineering boundaries working to resolve both silicon and system related manufacturing issues, providing ample opportunities to learn.
Key job responsibilities
- Work on improving our manufacturing data analysis and reporting systems to generate analysis which provide actionable information to improve key manufacturing metrics like yield, cost and coverage.
- Write python scripts, generate dashboards to automate analysis and generate alerts for team to review.
- Collaborate with ATE test, Foundry engineering and System validation teams to learn more about these test insertions and deep dive into manufacturing issues while supporting debug and root cause activities.
- Develop a good understanding of various ATE and System test coverage and work on activities to collect and analyze performance and power metrics on the latest and greatest workloads.
- Enrolled in a Bachelors’ degree program or higher in Electrical Engineering, Computer Engineering, or a related field with a graduation conferral date between December 2025 and September 2026
- Project OR internship experience with data analysis and automation using scripting languages like Python.
- Coursework or familiarity with basic semiconductor design process and manufacturing concepts.
- Prior internship/project based experience in data analysis and reporting, with a good understanding of statistics.
- Knowledge or experience with programming languages such as C , Java, Python and shell scripting.
- Familiarity with hardware or system design and testing process.
- Knowledge of foundry semiconductor manufacturing process.
- Familiarity with DFT concepts like Scan ATPG, Memory BIST testing.
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.
