Ph.D. Intern Architecture, DSP & Systems Architecture

About Marvell

Marvells 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

AI at hyperscale is an architecture problem. Training a frontier model across hundreds of thousands of XPUs routing over 100 terabits of traffic through a single switch fabric at 400 nanoseconds of latency processing optical signals at 1.6T across a data center floor none of it works without the systems architects DSP engineers and algorithm designers who define how data moves how signals are processed and how compute is organized at every layer of the stack. At Marvell that work happens across the full AI interconnect hierarchy: scale-up networks connecting XPUs within a rack using PCIe UAL and NVLink-compatible switching; scale-out fabrics interconnecting thousands of XPUs across rows and data center floors through the Teralynx Ethernet switch family purpose-built for AI now at 102.4 Tbps with 400ns latency on the T100; and scale-across connectivity linking geographically distributed data centers through coherent DSP and DCI platforms. The architecture decisions made here define what AI infrastructure can do at what speed and at what cost.

The work spans multiple disciplines and multiple markets. On the switching side teams are architecting the next generation of Teralynx switch silicon designing forwarding pipelines congestion control algorithms traffic management systems and telemetry architectures for AI fabrics running Ultra Ethernet Consortium protocols at 800G and 1.6T. On the DSP side teams are developing signal processing algorithms for high-speed optical and electrical links across PAM4 coherent and coherent-lite modulation formats work that spans data center interconnect carrier networking and emerging AI fabric applications. And on the systems side teams are defining the architecture of custom XPU connectivity platforms co-packaged optics integration and the end-to-end connectivity stack that hyperscalers depend on to scale their AI infrastructure.

Marvells Ph.D. Intern Program places doctoral candidates directly inside these active architecture and research efforts. Projects are selected because they sit at the intersection of Marvells most pressing systems-level challenges and the computer architecture signal processing theory and networking algorithms that define doctoral research in electrical engineering and computer science. The work is the applied dimension of the academic research a Ph.D. candidate is already pursuing conducted at production scale against real system constraints for hyperscale customers building the worlds most advanced AI infrastructure. What you will take away is something no simulation or academic dataset can replicate: the experience of seeing your architectural decisions and algorithms deployed in silicon running inside the worlds largest AI data centers.

What You Can Expect

As our Ph.D. Architecture DSP & Systems Intern every day you will work on systems-level problems that sit at the boundary of research and production where the algorithms and architectures you develop have direct consequences for how AI infrastructure performs at scale. Specifically you can expect to:

• Architect model and evaluate system-level designs for switching interconnect or DSP applications developing analytical models and simulations that inform real silicon architecture decisions

• Develop and optimize DSP algorithms for high-speed electrical or optical links including equalization FEC timing recovery and signal integrity techniques for PAM4 coherent or emerging modulation formats

• Design and analyze network architectures for AI fabrics including forwarding pipeline design congestion control traffic management and load balancing for scale-up scale-out and scale-across applications

• Collaborate with analog digital and software engineering teams to validate architectural assumptions against real hardware and silicon measurements

• Build behavioral models and simulations in MATLAB Python or C to evaluate performance tradeoffs across architecture power latency and bandwidth

• Present architectural proposals and algorithm results to engineering leadership and contribute to internal technical documentation and design reviews

What Were Looking For

To thrive in this role you must have hands-on research experience in computer architecture DSP or networking systems with the ability to move fluidly between theory and implementation. Specifically:

• Currently enrolled in a Ph.D. program in Electrical Engineering Computer Engineering Computer Science or a related field with a research focus in computer architecture digital signal processing communications systems or networking

• Demonstrate research experience in one or more of the following: processor or switch architecture DSP algorithm design for high-speed communications network protocol design or system-level modeling and simulation

• Apply strong analytical fundamentals whether in signal processing theory queuing theory information theory or computer architecture to real engineering problems with measurable performance targets

• Model and simulate complex systems using tools such as MATLAB Python or C/C; familiarity with hardware description languages (Verilog SystemVerilog) or cycle-accurate simulation is a plus

• Communicate architectural decisions and algorithm tradeoffs clearly you will present your work to engineering teams and defend your approach against real system constraints

Preferred Qualifications

• Familiarity with Ethernet switching architectures programmable forwarding pipelines or network congestion control algorithms for large-scale AI fabrics

• Experience with PAM4 coherent or high-speed serial link DSP including equalization FEC or timing and synchronization algorithms

• Exposure to custom compute architecture SoC design or XPU/GPU interconnect systems

• Knowledge of Ultra Ethernet Consortium (UEC) protocols RoCE or RDMA networking for AI workloads

• Experience with open networking platforms such as SONiC or P4-based programmable pipelines

Expected Base Pay Range (USD)

31 - 62 $ per hour.

The successful candidates 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 lifes 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 .

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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