About Marvell

Marvell's semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, automotive, 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

This team at Marvell develops Murals, a next-generation AI/ML infrastructure simulation and design platform that enables in-depth analysis and optimization of large-scale training and inference workloads. Leveraging trace-driven simulation, performance modeling, and hardware/software co-design, the team helps shape scalable and resilient solutions for advanced workloads such as LLMs, DLRMs, GenAI, and GNNs.

Working closely with system architects, hardware designers, and ML practitioners, the team explores innovative ways to optimize compute, memory, and networking subsystems across complex datacenter environments.

What You Can Expect

Simulation & Modeling - Implement workflows to study AI/ML workloads using trace-driven and analytical models.
Performance Analysis - Profile and analyze system bottlenecks across compute, memory, and network layers.
Networking Studies - Evaluate collective communication performance (all-reduce, all-to-all, reduce-scatter) across different topologies and fabrics.
Tooling & Automation - Develop utilities for trace generation, merging, conversion, and visualization.
Prototype & Validation - Test distributed training and inference pipelines in simulated and real environments.
Hardware/Software Co-Design - Collaborate on emerging technologies (CXL, DPUs, NVLink, PCIe, UET/UEC, in-network compute).
Scaling Studies - Conduct performance projections and trade-off studies for next-gen AI infrastructure.
Knowledge Sharing - Document workflows, publish internal reports, and drive peer learning.

What We're Looking For

Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or related field with 4-12 years of relevant professional experience.
Strong foundation in computer architecture, distributed systems, AI/ML, and operating systems.
Solid networking fundamentals including TCP/IP, RDMA, RoCE, UET/UEC, and switching/routing.
Experience with simulation frameworks (e.g., Astra-Sim, Chakra, gem5, SST, NS-3).
Hands-on with PyTorch/TensorFlow and distributed training frameworks (DDP, Horovod, DeepSpeed).
Strong programming skills in Python, C++, and scripting for automation.
Familiarity with interconnect and memory technologies (CXL, PCIe, NVLink, UAL).
Experience with profiling, telemetry, observability, and debugging tools.
Knowledge of collective communication algorithms and topology-aware scheduling.
Exposure to AI accelerators, memory disaggregation, DPUs, and custom silicon.
Familiarity with visualization tools (Perfetto, Chrome Tracing, Chakra Timeline, Flamegraphs).
Experience with large-scale AI training pipelines and scaling studies.
Interest in energy/performance trade-offs and resilience techniques.

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 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.

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.

#LI-MN1

Senior Staff AI/ML Scale Engineer