Network Site Reliability Engineer, AI Solutions Lab

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 The Solutions Architecture team sits within Marvell's Platform organization, which turns advanced silicon into deployable, customer-ready AI and cloud infrastructure. This team — the AI Solutions Lab — owns the validation layer that proves our platforms perform as promised, across compute, networking, and memory fabrics. Without it, Marvell could design great silicon but could never prove, at rack scale, that it performs the way customers expect — and hyperscalers don't buy chips on paper, they buy validated systems. Day to day, the team runs AI benchmarking experiments that mirror real customer workloads, operates GPU/HPC lab clusters, validates Marvell's Teralynx switching and AI fabrics under production-like conditions, and builds live demos for trade shows — carrying platform programs from concept to production. What sets this team apart is breadth of ownership: engineers here aren't limited to validating a single switch chip — they work across the full breadth of Marvell's AI platform portfolio, from Teralynx network fabrics to integrated optical platforms like co-packaged optics (CPO) and near-packaged optics (NPO), as well as emerging memory fabric products such as CXL and photonic fabric memory appliances. This cross-domain ownership — networking, optics, and memory, together — is work that's often siloed across separate teams elsewhere, and the results feed directly into customer proof points and executive reviews. What You Can Expect The NRE/SRE Engineer owns the compute and software foundation of the AI Solutions Lab. This role is responsible for building, standardizing, and operating the environments required to validate Marvell solutions across customer-relevant workloads, including scale-up, scale-out, memory acceleration, and DPU-enabled use cases. Key Responsibilities • Own compute provisioning, cluster bring-up, OS images, ROCm and NIC driver stacks, and environment standardization for lab systems. • Build and maintain MLPerf-style harnesses, workload libraries, test plans, result pipelines, and dashboards to support repeatable validation. • Establish baseline observability for cluster health, job execution, failures, utilization, and regression tracking. • Deploy and manage workload scheduling and orchestration (Kubernetes and/or Slurm) as the primary means of running validation and benchmark jobs across the lab. • Own incident response for lab infrastructure, driving root-cause analysis and reliability improvements after cluster or job failures. • Partner with architects, network engineers, and performance engineers to ensure lab environments accurately reflect target customer deployments. • Improve repeatability and operational efficiency through automation, infrastructure, code, and standardized workflows. • Support cross-functional validation efforts and help convert lab output into reusable internal and external assets. What We're Looking For Education and Certifications Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field; a PhD is a plus. Linux certifications, CKA certification, or similar Kubernetes certifications are preferred. Required Qualifications MS in Electrical/Computer Engineering, Computer Science, or related field; 6+ years of experience as a software/systems engineer, with at least 4+ years of Linux/infrastructure experience. Strong Linux systems experience at scale, including solid data center and cluster operations fundamentals; development experience across both Windows and Linux environments. Proficient in Python/TCL scripting and automation, with familiarity in C/C++ API development; proficiency in Python specifically for metrics, observability, and pipeline automation. Experience with automation tools such as Ansible and Terraform. Experience building and maintaining test harnesses, workload libraries, test plans, result pipelines, and dashboards to support repeatable validation. Experience establishing baseline observability for cluster/system health, job execution, failures, utilization, and regression tracking. Hands-on experience with workload scheduling and orchestration (Kubernetes and/or Slurm) in a lab or production environment. Excellent understanding of SW development flows, methodology, and production SW test policies and practices. Excellent interpersonal, written, and verbal communication skills; customer-facing experience required. Ability to handle multiple tasks simultaneously in a fast-paced lab environment Preferred Qualifications • Experience operating AI or HPC clusters in a lab or production environment. • Working familiarity with a distributed training framework (PyTorch DDP/FSDP, NeMo, or similar) sufficient to interpret job failures, not just infrastructure symptoms. • Working knowledge of at least one distributed-storage or parallel filesystem technology (e.g., Lustre, GPFS, BeeGFS, Ceph), since cluster performance is frequently storage-bound. • Basic experience with model tuning and workload optimization. Expected Base Pay Range (USD) 131,010 - 196,300, $ per annum The successful candidate’s 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. 
This role is eligible to participate in Marvell's bonus and equity plans, including a new hire equity grant and annual equity refreshers, ensuring you are rewarded for your contributions and remain invested in the company's long-term success.
 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 life’s most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights include an employee stock purchase plan with a 2-year look back, family support programs to help balance work and home life, robust mental health resources to prioritize emotional well-being, and a recognition and service awards to celebrate contributions and milestones. 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 TAOps@marvell.com . 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).