AI Infrastructure Engineering Intern- Master's Degree at Marvell Technology

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

31 Jan, 26

Salary

53.0

Posted On

02 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Data Analysis, Machine Learning, Generative AI, DSP, Data Visualization, Cloud Platforms, Data Pipeline Tools

Industry

Semiconductor Manufacturing

Description

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 existing and upcoming megatrends of cloud services, video streaming, 5G wireless and AI/ML among others, are driving the relentless demand for higher bandwidth, lower power and smaller footprint. Marvell offers a field proven solution for high-speed optical interconnects and transceivers that are utilized for a wide array of enterprise, carrier, small medium business, industrial and cloud data center applications. What You Can Expect Analyze and model DSP or other connectivity hardware test data to identify patterns, anomalies, and insights for device tuning. Develop and apply machine learning and generative AI models to optimize device interoperability, contributing to efficient hardware deployment. Collaborate with team members to automate data processing and integrate models into our testing workflows. Assist in creating documentation and visualizations for data analysis and model insights, leveraging tools like Python and related libraries. Stay updated with the latest in generative AI and hardware data analysis, proposing innovative approaches to improve device tuning and interop performance. What We're Looking For Must be currently enrolled in a master's program in Data Science, Computer Science, Electrical Engineering, or other related fields with an anticipated graduation date between Winter 2025 and Spring 2026 Proficiency in Python and experience with data analysis libraries (e.g., pandas, NumPy). Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and interest in generative AI. Strong analytical skills with attention to detail and ability to work independently on complex problems. Knowledge of DSP, other connectivity hardware or switching testing environments is a plus. Preferred Qualifications Experience with data visualization tools (e.g., Tableau, matplotlib) for presenting analysis and model results. Familiarity with cloud platforms (e.g., AWS, Azure) and data pipeline tools (e.g., Snowflake, Airflow) is a plus. Expected Base Pay Range (USD) 27 - 53, $ per hour. The successful candidate’s starting base pay will be determined based on job-related skills, experience, qualifications, work location and market conditions. The expected base pay range for this role may be modified based on market conditions. Additional Compensation and Benefit Elements For Internship roles, we are proud to offer the following benefits package during the internship - medical, dental and vision coverage, perks and discount programs, wellness & mental health support including coaching and therapy, paid holidays, paid volunteer days and paid sick time. Additional compensation may be available for intern PhD candidates. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Any applicant who requires a reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com. Interview Integrity As part of our commitment to fair and authentic hiring practices, we ask that candidates do not use AI tools (e.g., transcription apps, real-time answer generators like ChatGPT, CoPilot, or note-taking bots) during interviews. Our interviews are designed to assess your personal experience, thought process, and communication skills in real-time. If a candidate uses such tools during an interview, they will be disqualified from the hiring process. This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment. #LI-TT1 Join our talent community to hear about company news, job openings and events. Join our Talent Community! Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, automotive, 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. Recruitment fraud is a well-known way that third parties try to get personal information or to steal money from you. Please review Marvell’s guidance here to learn more on how you can protect yourself.

Responsibilities

Analyze and model DSP or other connectivity hardware test data to identify patterns and insights for device tuning. Collaborate with team members to automate data processing and integrate models into testing workflows.