Marvell Technology Logo

Marvell Technology

Network Site Reliability Engineer, Senior Staff AI Solutions Lab

Posted 16 Days Ago
Be an Early Applicant
In-Office
Santa Clara, CA, USA
131K-196K Annually
Senior level
In-Office
Santa Clara, CA, USA
131K-196K Annually
Senior level
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.
The summary above was generated by AI

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
HQ

Marvell Technology Santa Clara, California, USA Office

5488 Marvell Ln, Santa Clara, CA, United States, 95054

Similar Jobs

48 Minutes Ago
Hybrid
Livermore, CA, USA
17-28 Hourly
Junior
17-28 Hourly
Junior
eCommerce • Fashion • Retail • Sales • Wearables • Design
Leads sales-floor operations for a Coach retail store, drives sales targets and customer experience, develops and holds team members accountable, analyzes sales performance, supports recruiting and training, implements company initiatives, and ensures policy compliance. Provides customer-focused coaching, clienteling guidance, HR and conflict-resolution support, and helps build an inclusive, high-performing team while supporting store leadership and operational goals.
6 Hours Ago
Hybrid
90K-115K Annually
Senior level
90K-115K Annually
Senior level
Fashion • Retail • Sports
Own paid media strategy and execution across Meta, Google, TikTok, and emerging channels. Manage campaign architecture, budgets, bidding, product feeds, creative testing, reporting, attribution, and incrementality testing. Build dashboards, forecast budgets with Finance, and partner with Ecommerce, Retention, Brand, and Merchandising on launches and promotions. Evaluate vendors and optimize acquisition and retargeting performance using ROAS, CAC, MER, and contribution metrics.
Top Skills: Affiliate MarketingAi ToolsCtvGa4Google AdsLookerMeta Ads ManagerNorthbeamOmniPerformance MaxPinterestRedditRockerboxShopifySmart BiddingSnapchatTableauTiktok AdsTriple Whale
6 Hours Ago
Hybrid
150K-180K Annually
Senior level
150K-180K Annually
Senior level
Cloud • Legal Tech • Marketing Tech • Payments • Software
Own and define Dubsado’s data infrastructure strategy, including pipelines, warehouse reliability, analytical modeling, data quality, observability, and tooling standards. Build scalable data systems, collaborate with engineering, product, and business teams, and support AI agents, customer-facing features, and internal users. Serve as the initial dedicated data specialist, operating autonomously while gradually distributing data quality ownership across engineering.
Top Skills: BigQueryClaude CodeCursorDbtHevoMetabaseMongoDBObservablePosthogSQL

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account