Product Development Engineer Intern (Co-op) - AI/Hardware

AMD; Santa Clara (CA); Hybrid; USD 47,000 - 60,000; Full time

Benefits offered by this job

AMD benefits

Job summary

AMD is seeking a master's student for a Co-op/Intern role in Santa Clara, focusing on characterization and test program development for next‑gen microprocessors. You will work with Product Development Engineers to build production test programs and perform engineering studies to support yield and ramp.

Collaborate with multi‑functional teams to resolve production issues, document technical work, and gain hands-on experience in a fast‑paced AI ecosystem.

Qualifications

• Currently enrolled in a US-based university in a Master's degree program majoring in Computer Science, Computer Engineering, Electrical Engineering or related field.
• Strong interest in building production test programs and data analysis for semiconductor devices.
• Experience with version control and agile processes is a plus.

Responsibilities

• Support Product Development Engineers in characterization and to build production test programs through parametric, data and statistical analysis.
• Perform engineering and correlation studies to ensure yield, coverage and ramp goals.
• Collaborate with multi-functional teams to resolve production-related issues and improve efficiency.
• Build and maintain technical documents and debug manufacturing/test programs for next-generation AMD processors.
• Participate in product debug and characterization to identify performance sensitivities.

Skills

C++

Linux

Shell scripting

Java

Git/SVN/CVS

Agile/Scrum/Kanban

Education

Master's degree in CS/CE/EE

Tools

Git

SVN

CVS

RCS

Job description

AMD is seeking a master's student for a Co-op/Intern role in Santa Clara, focusing on characterization and test program development for next‑gen microprocessors. You will work with Product Development Engineers to build production test programs and perform engineering studies to support yield and ramp.

Collaborate with multi‑functional teams to resolve production issues, document technical work, and gain hands-on experience in a fast‑paced AI ecosystem.