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Location
In office (Santa Clara)
Seniority
Intern
Employment
Internship

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 6, 2026. Marvell Technology scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Marvell Technology is an American fabless semiconductor company founded in 1995 that designs the infrastructure silicon behind data centres, carrier networks and storage systems. Its portfolio covers electro-optics and digital signal processors for optical links, ethernet switching and physical layer devices, storage controllers, and custom application specific integrated circuits designed for individual cloud operators. Headquartered in Santa Clara and listed on Nasdaq, it reoriented itself over the past decade from consumer and storage chips toward data centre and artificial intelligence infrastructure, which now supplies the majority of its revenue.

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 Machine Learning Platform team develops and operates the infrastructure that powers large-scale AI and machine learning workloads. The team focuses on enabling scalable, reliable, and efficient ML operations across distributed computing environments, supporting model training, deployment, monitoring, and optimization. Working at the intersection of AI/ML and systems engineering, the team drives performance, resource efficiency, and operational excellence for next-generation AI platforms.

What You Can Expect

  • Monitor and analyze AI platform performance across distributed computing environments.
  • Identify opportunities to optimize machine learning training and inference workloads.
  • Support GPU cluster and cloud infrastructure capacity planning and resource management.
  • Evaluate model deployment performance, including latency, throughput, and scalability metrics.
  • Troubleshoot system performance issues and infrastructure challenges impacting ML workloads.
  • Collaborate with cross-functional engineering teams to improve AI infrastructure and platform efficiency.
  • Enhance data pipeline and storage performance for large-scale machine learning applications.

What We're Looking For

  • Currently pursuing a Bachelor’s or Master's degree in Computer Science, Computer Engineering, or a related technical field with an expected graduation date between Fall 2027 and Summer 2028
  • Proficiency in Python for manipulation and analysis
  • Knowledge of GPU computing, CUDA programming, networking fundamentals, and distributed systems concepts
  • Familiarity with distributed computing environments, cloud platforms (AWS, GCP, Azure), and containerization technologies such as Docker and Kubernetes
  • Understanding of system monitoring, logging, and performance analysis concepts
  • Strong analytical and problem-solving skills, with experience in data analysis and visualization
  • Exposure to machine learning workflows, model deployment, and lifecycle management.
  • Strong written and verbal communication skills, with the ability to present technical findings to diverse stakeholders

Expected Base Pay Range (USD)

29 - 57, $ 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

Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life’s most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights for our interns: medical, dental, and vision coverage, perks and discounts, robust mental health resources to prioritize emotional well-being, and paid holidays. Additional compensation may be available for intern PhD candidates. We look forward to sharing more with you during the interview process.

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 [email protected].

Interview Integrity

To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews.

These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification 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.

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