Research Intern (PhD), Storage Systems for AI
About Marvell
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
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
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
Additional Compensation and Benefit Elements
Interview Integrity
Not included in the source posting: what you'll do, qualifications.
Skills
Who can apply
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