Research Intern (PhD), AI-Scale Protocols & Simulation

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: Explore how tomorrow's AI networks will behave at scale — using simulation to study scale-up and scale-out protocols, congestion, and the interplay between workloads, fabrics, and hardware before they ever reach silicon.

Investigate emerging scale-up and scale-out protocols and how they perform under real AI workloads Explore and extend simulation platforms to model networking and congestion-control behavior at scale Experiment with AI-scale and LLM-serving simulation, and workload/trace-driven modeling (e.g., Astra-Sim, Chakra, htsim) Study and evaluate protocol performance, scalability, and resilience across topologies Correlate simulation results with architectural and hardware behavior to uncover new insights 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 or a related field.

Strong fundamentals in computer networks, transport protocols, and distributed systems Curiosity about large-scale simulation and a desire to work with frameworks such as Astra-Sim, Chakra, htsim, ns-3, gem5, or SST Understanding of scale-up/scale-out fabrics, RDMA, or congestion control — or eagerness to go deep Programming in C++ and Python Preferred: Interest in LLM-serving and AI-workload simulation, next-generation datacenter networking, protocol design, or large-scale performance analysis. 

 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