Accelerated Computing Solutions Analyst - Early Career

Marvell Technology • Santa Clara, CA

1d

About The Position

The Technology and Solutions Architecture team is innovating at the intersection of hardware and software— Building co-optimized solutions for the most demanding AI data center challenges, reimagining the data- movement / storage / transformation / processing pipelines with purpose-built Marvell accelerators to advance next-generation AI infrastructure, and shaping open standards. We are seeking an innovative AI Solutions Analyst to research, explore, and build co-optimized fabric-attached, shared, disaggregated, and multi-tier memory and storage solution architectures designed to meet the rapidly scaling memory and storage demands of XPU for increasingly data-centric workloads. You will work closely with architects, technologists, and product teams to influence research and development in cutting-edge forward-looking technologies in the disaggregated memory, storage, networking, and security domains.

Requirements

• PhD or Master's degree in computer science and engineering, electrical engineering, or related field
• HW/SW co-design experience with proven expertise with GPUs, DPUs, FPGAs, or custom hardware accelerators
• Processor micro-architectures (preferably ARM), scalar and vector processing pipelines, techniques to optimize memory bound applications
• Deep understanding of memory or storage subsystems, disaggregated memory for accelerators, cluster level shared memory approaches, NVMeoF
• Familiarity with coherent / non-coherent interconnects, like CXL, UAL, NVLink, and multi-GPU / multi-node communication mechanisms and optimization techniques like SHARP and NCCL
• Proficiency in performance benchmarking of AI data processing workloads, system profiling and analyzing end-to-end flows
• Experience with simulators & modeling, GPU/CPU cooperative accelerated computing optimizing / accelerating data-centric AI workloads

Responsibilities

• Partner with hardware and software architects, technologists, and IC engineering teams to develop scalable, high-performance, cutting-edge AI/ML infrastructure.
• Spearhead advancements in accelerating AI/ML applications in heterogenous and disaggregated compute architectures, networking, storage, and security domains, focusing on emerging technologies such as CXL, UAL, UEC, low-latency transport protocols, and Post-Quantum Cryptography.
• Lead system architectural design and implement proof-of-concept solutions for diverse workloads, optimizing execution across distributed, heterogeneous memory, compute, and storage environments.
• Present innovative ideas and substantiated proof-points to senior management and CTOs.
• Advocate Marvell’s leadership in industry standards bodies and working groups, shaping new standards and emerging technologies aligned with Marvell's strategic interests.
• Conduct advanced characterization and performance analysis of complex workloads, monitoring critical metrics such as response time, latency, and resource utilization.
• Create and refine simulation environments for large-scale setups and configurations, especially in the AI/ML domain.
• Develop comprehensive documentation and data visualizations to support analysis and insights, leveraging tools like Python and related libraries.
• Keep abreast of the latest developments in generative AI and hardware data analysis, and propose innovative approaches to enhance device tuning and interoperability performance.

Benefits

• employee stock purchase plan with a 2-year look back
• family support programs
• robust mental health resources
• recognition and service awards

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 1,001-5,000 employees