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…