Machine Learning Operations Product Development Engineering Intern
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Job Description
About the Company:
Amazon Web Services (AWS) is a major player in cloud computing. Within AWS, Annapurna Labs is at the forefront of hardware co-design, creating cutting-edge, internet-scale hardware and software for accelerated computing (both Machine Learning and FPGA acceleration). They design and build every component, from silicon creation to managing the full lifecycle of their systems at a massive scale. The team focuses on developing the silicon used in advanced machine learning accelerator servers, utilizing cutting-edge process nodes. Their work results in servers used in massively scaled clusters to provide optimal hardware platforms for customer workloads.
Detailed Job Description:
This is a full-time (40 hours/week) 12-week summer internship within the AWS-Annapurna team’s Machine Learning operations product development engineering group. The internship focuses on optimizing key manufacturing metrics (yield, test cost, test coverage) for their machine learning accelerator products. This involves working across ATE test and System test insertions. Responsibilities also include power/performance characterization of new silicon, aiming to optimize system power/performance with adaptive scaling schemes and improving foundry processes.
Key Responsibilities:
• Improve manufacturing data analysis and reporting systems: Generate actionable analyses to improve key metrics (yield, cost, coverage). This involves writing Python scripts and creating dashboards to automate analysis and generate alerts.
• Collaborate with cross-functional teams: Work with ATE test, Foundry engineering, and System validation teams to investigate and resolve manufacturing issues, supporting debug and root cause analysis.
• Develop understanding of ATE and System test coverage: Collect and analyze performance and power metrics on the latest workloads.
• Work beyond traditional silicon product engineering: Solve both silicon and system-related manufacturing issues, expanding skillset beyond silicon engineering.
Qualifications:
• Basic Qualifications:
• Enrolled in a Bachelor’s degree program or higher (Electrical Engineering, Computer Engineering, or related field) with a graduation 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.
• Preferred Qualifications:
• Prior internship/project experience in data analysis and reporting, with a good understanding of statistics.
• Knowledge/experience with programming languages (C++, Java, Python, shell scripting).
• Familiarity with hardware or system design and testing processes.
• Knowledge of foundry semiconductor manufacturing processes.
• Familiarity with DFT concepts (Scan ATPG, Memory BIST testing).
The internship offers opportunities to learn and contribute to a significant project within a large-scale organization.
