Test Solutions Engineer Intern - Bachelors Degree (2603835)

About Marvell

Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities. 

At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead. 

Your Team, Your Impact

The Operations team at Marvell is seeking a curious and driven Test Solutions Engineering (Post-Silicon Hardware Validation) Intern to join our team for a hands-on experience working

with cutting-edge silicon technologies. This internship offers a unique opportunity to work alongside experienced engineers in the validation of custom silicon and the development of test requirements for Marvell data center applications.

Interns will gain exposure to multiple aspects of the custom silicon business, including design, process technology, and test methodology. You'll play a key role in analyzing test data, supporting lab evaluations, and contributing to the resolution of circuit-level issues.

What You Can Expect

• Analyze test data from silicon devices to identify trends and anomalies.
• Develop basic scripts and tools using Python, Perl and R to support data analysis and test automation.
• Collaborate with cross-functional teams to define test requirements and validation goals.
• Document findings and contribute to team discussions on issue resolution.

What We're Looking For

• Candidate must be currently pursuing a BS degree in Electrical Engineering, Computer Engineering or related technical field(s), graduating in December 2027 or May 2028.

Preferred Qualifications:

• Understanding of semiconductor devices, circuit behavior and test methodologies.
• Strong analytical thinking and communication skills.
• Knowledge of basic statistics and data visualization techniques.
• Familiarity with scripting languages such as Python, Perl, or R in a Linux environment.
• Enthusiasm for problem-solving in a collaborative environment.