Network Site Reliability Engineer, AI Solutions Lab

Posted 6 Days Ago
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Santa Clara, CA, USA
In-Office
131K-196K Annually
Senior level
Artificial Intelligence • Automotive • Semiconductor
We create custom semiconductor solutions that move, process, store, and secure data quickly and reliably.
The Role
Build, standardize, and operate compute and software infrastructure for AI and HPC validation labs. Responsibilities include cluster provisioning, Linux images, drivers, Kubernetes or Slurm orchestration, benchmark harnesses, workload libraries, observability, dashboards, incident response, root-cause analysis, and automation. The role partners with architecture and performance teams to mirror customer deployments and support repeatable validation across AI, networking, memory, and DPU use cases.
Summary Generated by Built In

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 [email protected].

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). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.

#LI-AO1

Skills Required

  • Master's degree in Electrical or Computer Engineering, Computer Science, or a related field
  • 6+ years of software or systems engineering experience
  • At least 4+ years of Linux or infrastructure experience
  • Strong Linux systems experience at scale, including data center and cluster operations fundamentals
  • Development experience across Windows and Linux environments
  • Proficiency in Python and TCL scripting and automation
  • Familiarity with C/C++ API development
  • Experience with Ansible and Terraform
  • Experience building test harnesses, workload libraries, test plans, result pipelines, and dashboards
  • Experience establishing observability for cluster or system health, job execution, failures, utilization, and regression tracking
  • Hands-on experience with Kubernetes and/or Slurm workload scheduling and orchestration
  • Understanding of software development flows, methodology, and production software test practices
  • Excellent interpersonal, written, and verbal communication skills
  • Customer-facing experience
  • Ability to handle multiple tasks in a fast-paced lab environment
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • PhD in a related field
  • Linux certification, CKA certification, or similar Kubernetes certification
  • Experience operating AI or HPC clusters
  • Familiarity with distributed training frameworks such as PyTorch DDP/FSDP or NeMo
  • Knowledge of distributed storage or parallel filesystems such as Lustre, GPFS, BeeGFS, or Ceph
  • Basic experience with model tuning and workload optimization

Marvell Technology Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Marvell Technology and has not been reviewed or approved by Marvell Technology.

  • Equity Value & Accessibility — Equity appears to be a meaningful part of total rewards through RSUs and an ESPP with a 15% discount and lookback, which can materially raise overall compensation. Stock upside is positioned as a key differentiator when company performance is strong.
  • Parental & Family Support — Paid parental/bonding leave is described as substantial, with additional disability leave for birthing parents and a flexible return-to-work program. Family-care leave, generous bereavement provisions, and family-building support (e.g., adoption/surrogacy reimbursement) further strengthen the package.
  • Healthcare Strength — Medical coverage is presented as broad with multiple plan options and preventive care covered at 100% in-network, alongside dental, vision, and structured mental-health support. Additional programs like telehealth and specialized care partners add depth to the health offering.

Marvell Technology Insights

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The Company
HQ: Santa Clara, CA
6,500 Employees
Year Founded: 1995

What We Do

Marvell specializes in semiconductor solutions that power a wide range of industries, from data centers and 5G networks to AI, automotive, and storage applications. Our cutting-edge products are designed to meet the constantly evolving demands of a connected world, enabling faster, more efficient and more secure data processing and communication. With a focus on excellence and a commitment to advancing technology, we develop solutions that drive progress and transform industries.

Why Work With Us

Life at Marvell means being a part of new innovation and enduring technology; but it's also much more. Our diverse community is strengthened through cultural events, corporate gatherings and team-building activities, fostering collaboration and making work enjoyable. At Marvell, it's not just a job; it's an enriching, community-driven experience.

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