--- title: 'Network Analyst at Lambda' canonical: 'https://feeny.ai/job/network-analyst-lambda-san-francisco-789ycevmdbne' type: 'job' last_seen: '2026-10-18' --- # Network Analyst at Lambda - **Company:** Lambda - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-09 - **Last confirmed live:** 2026-10-18 - **Apply:** https://jobs.ashbyhq.com/lambda/cea27d13-db06-4027-9007-a1a4cd820662 ## Job description Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU. If you'd like to build the world's best AI cloud, join us. *Note: This position requires presence in our San Francisco or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. ## About the Role Build your networking career by helping connect Lambda’s AI compute to customers and carriers. You’ll follow real services from order through installation and testing, working alongside engineers and delivery managers. You’ll join the Network Planning and Delivery team within Cloud and AI Networking and learn how fiber, optics and carrier services become a working network. You’ll start with approved service requests and network records, then take on testing and automation work as your skills develop. This is an early-career network role with guidance from experienced teammates and responsibility for work the team relies on. The details you check and the requests you follow through help get new services online and keep the network accurately documented. ## What You’ll Do Help Bring Services Online - Submit approved cross-connect orders after confirming circuit identifiers and endpoints with Network Engineering. - Track carrier and facility requests through completion, follow up on installation dates and flag delays or mismatched details. - Arrange approved disconnections after confirming the service and timing with its owner, and collect completion records. - Log new requests in Jira, route them to the right owner and coordinate approved access to carrier and data center portals. Support Engineering and Testing - Help engineers prepare turn-up documents, gather test results and check service details before activation. - Support circuit turn-up and testing under a senior engineer’s direction, learning how to investigate discrepancies and document findings. - Learn the team’s tools and contribute scripts or workflow improvements that reduce repeat manual work. Keep Service Information Reliable - Maintain circuit records, supplier contacts and project updates so engineers and delivery managers can find the information they need. - Organize order confirmations, test evidence and support details for handover to Operations. - Share completed service changes with Supply Chain for purchasing and billing updates, and raise discrepancies with the delivery manager. You - Foundational networking knowledge from work, study, labs or personal projects, including how fiber and optics connect equipment. - Examples of following a technical task through completion and checking that the result matches the request. - Comfort organizing information in ticketing tools, spreadsheets or similar systems. - Clear written communication and the judgment to ask for help before acting on an unclear request. - Interest in learning physical network infrastructure and taking on more technical responsibility over time. ## Nice To Have - Networking coursework or a certification such as Cisco Certified Network Associate (CCNA). - Exposure to data center work, carrier provisioning, technical support or network inventory tools such as NetBox. - Some Python or other scripting experience, including coursework or personal projects. We Are Looking for Someone Who Is - Curious about how a network gets built beyond the configuration screen. - Careful with details and willing to speak up when something does not look right. - Eager to learn from teammates and use feedback on the next task. Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. ## About Lambda - Founded in 2012, with 500+ employees, and growing fast - Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove - We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG - Our values are publicly available: https://lambda.ai/careers - We offer generous cash & equity compensation - Health, dental, and vision coverage for you and your dependents - Wellness and commuter stipends for select roles - 401k Plan with 2% company match (USA employees) - Flexible paid time off plan that we all actually use ## Equal Opportunity Employer Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law. ## About Lambda ## Company Overview - **One-liner**: Lambda builds supercomputers and cloud infrastructure for training and deploying large-scale AI models, from single GPUs to gigawatt-scale AI factories. - **Entity Type**: Private (funding stage not publicly disclosed; founded by ML engineers) - **Headquarters**: San Francisco, California, USA - **Founded**: 2012 - **Founders**: Stephen Balaban and Michael Balaban ## Core Business - Primary industry: AI infrastructure / cloud computing for machine learning. - Target customers: Frontier AI labs building large foundation models, hyperscalers scaling global AI infrastructure, and enterprises deploying AI in regulated industries (B2B, Enterprise). - Mission: “Make compute as ubiquitous as electricity and give everyone in America the power of superintelligence” (also “One person, one GPU”). ## Products & Services - **The Superintelligence Cloud**: A suite of cloud computing offerings specifically built for AI workloads, including: - **GPU Instances**: On-demand NVIDIA HGX B200, H100, and GB300 NVL72 instances for prototyping and testing. - **Managed Clusters**: Dedicated, single-tenant clusters (e.g., NVIDIA GB300 NVL72, HGX B200/H100) with full management and co-engineering from Lambda’s team. - **1-Click Clusters™**: Rapidly deployable clusters for training and inference. - **Superclusters**: Large-scale AI factories integrating high-density power, liquid cooling, and high-bandwidth interconnects. - **AI Infrastructure Hardware**: Modular AI factory designs and NVIDIA-based systems for on-premise or colocation deployment. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed. - **Key Metric**: Total funding not publicly available; revenue not disclosed. - **Notable Customers/Partners**: “World’s most advanced AI organizations” (frontier labs, hyperscalers, regulated enterprises). Leadership includes former executives from cloud and networking companies. - **Growth Signals**: Active hiring across engineering, storage, security, and procurement roles; building AI factories at gigawatt scale; SOC 2 Type II certified; expanding from San Francisco to San Jose, CA. ## Competitive Advantages - **AI‑First DNA**: 100% of engineering, operations, and support dedicated to AI – founded by ML engineers in 2012. - **Single‑Tenant Isolation**: Shared‑nothing architecture for security and performance, with hardware‑level isolation. - **Full‑Stack Expertise**: Co‑engineering from the same team building the infrastructure, enabling deep optimization for large training runs. - **Hacker Culture**: Rooted in the Noisebridge hackerspace values of do‑ocracy, low ego, and “be excellent to each other.” - **Performance**: Rack‑scale NVIDIA systems (GB300, B200, H100) with high‑speed interconnects (NVIDIA Quantum‑2 InfiniBand). ## Strategic Focus - Scaling infrastructure to support the next generation of superintelligence, including gigawatt‑scale AI factories. - Enabling frontier labs to train trillion‑parameter models and serve billions of tokens in production. - Expanding compliance and security capabilities for regulated industries. - Growing the cloud platform (The Superintelligence Cloud) as the primary go‑to‑market offering. ## Why Work Here - **Culture**: Hacker ethos (Noisebridge roots), low ego, no yelling, no politics, no crypto. Values: build, move fast, care, be excellent to each other. - **Work Environment**: Fast‑paced, high‑change, outcome‑focused. Emphasis on technical excellence and curiosity. Anonymous feedback encouraged. - **Interview Process**: Clear, structured steps (recruiter chat → hiring manager → technical assessment → panel interviews → reference/offer). Pedigree is not everything; focus on what you’ve built. - **Location & Remote**: Offices in San Francisco and San Jose, CA. FAQ page addresses remote/hybrid policy (details not provided in available snippets); some roles appear on‑site. - **Perks**: Benefits, time off, and other perks are listed on the careers site (specifics not extracted here). ## Sources 1. [lambda.ai/about](https://lambda.ai/about) 2. [lambda.ai/](https://lambda.ai/) 3. [lambda.ai/careers](https://lambda.ai/careers) 4. [lambda.ai/leadership](https://lambda.ai/leadership) ## Other roles at Lambda - [Senior Finance Systems Architect](https://feeny.ai/job/senior-finance-systems-architect-lambda-san-francisco-xm8j0m2v06c8) — San Francisco, CA - [Senior Analyst - Investor Relations](https://feeny.ai/job/senior-analyst-investor-relations-lambda-san-francisco-k9fx1taykgcb) — San Francisco, CA - [Principal Product Manager - Console](https://feeny.ai/job/principal-product-manager-console-lambda-bellevue-grhs8jsg305p) — Bellevue, WA - [Lead / Staff Full-Stack Software Engineer - Console Experience](https://feeny.ai/job/lead-staff-full-stack-software-engineer-console-experience-lambda-san-francisco-5vc6y6f42h61) — San Francisco, CA - [Controller](https://feeny.ai/job/controller-lambda-san-jose-6aq9p2xm7a59) — San Jose, CA - [Head of Tax](https://feeny.ai/job/head-of-tax-lambda-san-francisco-w2mk4rcpsp9w) — San Francisco, CA - [Staff Product Manager - Observability](https://feeny.ai/job/staff-product-manager-observability-lambda-bellevue-5t09nw1b5snq) — Bellevue, WA - [Technical Program Manager - Data Center Infrastructure Delivery](https://feeny.ai/job/technical-program-manager-data-center-infrastructure-delivery-lambda-united-4ke422t8s71r) — United States - [Network Planning & Design Manager](https://feeny.ai/job/network-planning-design-manager-lambda-san-francisco-y6e7f7epjkxy) — San Francisco, CA - [Network Infrastructure Delivery Manager](https://feeny.ai/job/network-infrastructure-delivery-manager-lambda-san-francisco-8xzaptr7xkjt) — San Francisco, CA