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Marvell

High-performance semiconductor solutions for data infrastructure

Network Site Reliability Engineer Senior Staff - AI Solutions Lab

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeSanta Clara, CA, USAIn-person

About the Job

Requirements

  • A master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, and at least 6 years of experience as a software or systems engineer, including at least 4 years of Linux or infrastructure experience.
  • Strong Linux systems experience at scale, including data center and cluster operations fundamentals, and development experience in both Windows and Linux environments.
  • Proficiency in Python and TCL scripting and automation, familiarity with C/C++ API development, and proficiency in Python 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 for repeatable validation.
  • Experience establishing baseline observability for cluster or system health, job execution, failures, utilization, and regression tracking.
  • Hands-on experience with workload scheduling and orchestration using Kubernetes and/or Slurm in a lab or production environment.
  • Excellent understanding of software development flows, methodology, and production software test policies and practices.
  • Customer-facing experience is required.
  • Ability to handle multiple tasks simultaneously in a fast-paced lab environment.

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 using Kubernetes and/or Slurm as the primary means of running validation and benchmark jobs across the lab.
  • Own incident response for lab infrastructure and drive 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.

Desired Qualifications

  • Experience operating AI or HPC clusters in a lab or production environment.
  • Working familiarity with a distributed training framework such as PyTorch DDP/FSDP, NeMo, or similar, sufficient to interpret job failures beyond 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.
  • Linux certifications, CKA certification, or similar Kubernetes certifications.
  • A PhD.

About the Company

Marvell

High-performance semiconductor solutions for data infrastructure

Marvell Technology, Inc. creates high-performance semiconductor products that power data infrastructure for telecommunications operators, data centers, and enterprises. Its offerings span computing, storage, and networking to enable efficient, secure data transmission, storage, and processing. The products are programmable and scalable platforms designed for high bandwidth and strong security, supporting 5G networks and the broader digital economy. Revenue comes from designing, manufacturing, licensing, and providing related services to other businesses that integrate these components into their own products. Unlike many peers, Marvell emphasizes programmable, scalable platforms tailored to data infrastructure needs and long-term partnerships with enterprise and telecom customers. The company aims to help customers upgrade their networks and data systems to increase capacity, performance, and efficiency while expanding its own business in the data infrastructure space.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1995

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