Network Site Reliability Engineer, AI Solutions Lab

Marvell Technology • Santa Clara, CA

8h

About The Position

The Network Site Reliability Engineer (NRE/SRE) owns the compute and software foundation of Marvell’s AI Solutions Lab within the Solutions Architecture team. The role builds, standardizes, and operates environments used to validate Marvell solutions against customer-relevant workloads, including scale-up, scale-out, memory acceleration, and DPU-enabled use cases. The team validates platforms across compute, networking, and memory fabrics, operates GPU/HPC lab clusters, runs AI benchmarking experiments, and supports live demonstrations and customer proof points.

The engineer is responsible for cluster provisioning and operations, workload scheduling and orchestration, automation, test and result infrastructure, and baseline observability. The role works with architects, network engineers, and performance engineers to ensure lab environments reflect target customer deployments and turns lab output into reusable internal and external assets.

Requirements

• Master’s degree in Electrical/Computer Engineering, Computer Science, or a related field.
• At least 6 years of experience as a software/systems engineer, including at least 4 years of Linux/infrastructure experience.
• Strong Linux systems experience at scale, including data center and cluster operations fundamentals.
• Development experience across both Windows and Linux environments.
• Proficiency in Python/TCL scripting and automation; Python experience specifically for metrics, observability, and pipeline automation.
• Familiarity with C/C++ API development.
• Experience with automation tools such as Ansible and Terraform.
• Experience building and maintaining test harnesses, workload libraries, test plans, result pipelines, and dashboards for 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 software development flows, methodology, and production software test policies and practices.
• Excellent interpersonal, written, and verbal communication skills; customer-facing experience is required.
• Ability to handle multiple tasks simultaneously in a fast-paced lab environment.

Nice To Haves

• PhD in a related field.
• Linux certifications, CKA certification, or similar Kubernetes certifications.
• Experience operating AI or HPC clusters in a lab or production environment.
• Working familiarity with a distributed training framework such as PyTorch DDP/FSDP or NeMo, sufficient to interpret job failures and distinguish them from infrastructure symptoms.
• Working knowledge of at least one distributed-storage or parallel filesystem technology, such as Lustre, GPFS, BeeGFS, or Ceph.
• Basic experience with model tuning and workload optimization.

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 for repeatable validation.
• Establish baseline observability for cluster health, job execution, failures, utilization, and regression tracking.
• Deploy and manage workload scheduling and orchestration, using Kubernetes and/or Slurm as the primary means of running validation and benchmark jobs across the lab.
• Own incident response for lab infrastructure, conduct root-cause analysis, and drive 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.

Benefits

• Bonus and equity plans, including a new hire equity grant and annual equity refreshers.
• Employee stock purchase plan with a 2-year look back.
• Family support programs.
• Mental health resources.
• Recognition and service awards.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior