Research Intern - Storage Systems for AI

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

Marvell is a global leader in high-performance silicon and AI infrastructure, powering the world's most advanced datacenters, cloud platforms, 5G networks, and AI/ML workloads. Our innovations drive next-generation computing, networking, and storage — enabling breakthrough performance, scalability, and efficiency for the most demanding applications.

Why This Internship

* Engage with open research problems at the frontier of AI systems — challenges that require access to real silicon, large-scale infrastructure, and production data
* Contribute to work intended for publication, with support for presenting results both internally and externally
* Translate research outcomes into real products and next-generation silicon, extending impact beyond publication
* Collaborate with and receive mentorship from senior architects and researchers who will help advance your ideas
* Gain access to advanced infrastructure, tools, and pre-release hardware rarely available in academic settings
* Pursue original, exploratory research directions — independent thinking is actively encouraged

What You Can Expect

Focus: Next-generation storage and memory systems for AI — spanning NVMe, storage software, memory tiering, disaggregation, and near-data computing.

Key Responsibilities

• Explore next-gen storage and memory architectures for AI/ML workloads
• Work with NVMe and storage software stacks (e.g., SPDK) for high-performance data access
• Investigate memory/storage tiering and disaggregation for large-scale AI systems
• Explore computational/near-storage techniques — quantization, compression, predictive caching, and data migration
• Prototype and evaluate storage architectures for performance, scalability, and efficiency

What We're Looking For

Eligibility: Enrolled in a PhD, MS by Research, or MTech by Research program in Computer Science, Computer Engineering, electronics or Electrical Engineering, Robotics or a related field.

Requirements

• Strong fundamentals in computer architecture, storage systems, and operating systems
• Familiarity with storage technologies and stacks (NVMe, SPDK, SSDs, memory hierarchies)
• Understanding of ML data pipelines or workload characteristics
• Programming in C/C++ and Python

Preferred: Exposure to memory disaggregation, storage tiering, near-data computing, or high-performance I/O.





Additional Compensation and Benefit Elements

With competitive compensation and great benefits, you will enjoy our workstyle within an environment of shared collaboration, transparency, and inclusivity. We’re dedicated to giving our people the tools and resources they need to succeed in doing work that matters, and to grow and develop with us. For additional information on what it’s like to work at Marvell, visit our Careers page.

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.

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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