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 Bellevue or San Francisco office location 4 days per week; Lambda's designated work from home day is currently Tuesday.

About the Role

Lambda's hardware is the product. Every training run, fine-tune, and inference workload our customers launch runs on hardware someone at Lambda decided to buy, configure, and ship as a product. This role owns that decision. You'll manage the GPU (graphics processing unit) fleet lifecycle as a product: new NVIDIA platform introductions such as the B200 and H200 class and the generations that follow, node and cluster configurations, InfiniBand fabric options, and the roadmap for what hardware Lambda offers, when, and at what configuration.

You'll sit at the layer where Lambda meets silicon. Externally, you'll work directly with NVIDIA and with ODM (original design manufacturer) partners on roadmap alignment. Internally, you'll work with our data center, supply chain, and infrastructure engineering teams to turn silicon roadmaps into sellable, reliable products: On-Demand GPU Instances, 1-Click Clusters, and our largest multi-node reserved deployments. You'll translate customer demand signals and benchmark data into fleet investment recommendations that shape where Lambda puts its capital.

Great product managers at Lambda are defined by three things: insight, influence, and execution. Insight means you look at the data, determine what it means for customers and business, and then figure out what to do about it. But, a great idea doesn’t mean anything in a vacuum. That is where influence comes in. Influence means you take that idea and get others to want to buy into it; you win over engineers, designers, executives, and partners without relying on authority. But a great idea that everyone is excited about doesn’t matter unless it is delivered to customers. Execution means you work with the right people to get the idea launched, then measure and iterate. We hire product managers who learn new domains fast and reason rigorously from evidence. Deep background in GPU hardware, systems, or the semiconductor ecosystem are also desired.

We value diverse backgrounds, experiences, and skills, and we are excited to hear from candidates who can bring unique perspectives to our team. If you do not exactly meet this description but believe you may be a good fit, please still apply and help us understand your readiness for this role.

What You'll Do

• Own the Hardware Roadmap: Define what GPU platforms Lambda offers, when, and at what configuration, from today's B200 and H200 class systems through next-generation NVIDIA platforms.

• Drive New Platform Introductions: Lead new NVIDIA platform introductions end to end, from early roadmap alignment through general availability as On-Demand GPU Instances and 1-Click Clusters.

• Translate Demand Into Investment: Turn customer demand signals and benchmark data into fleet investment recommendations, and defend those recommendations with executives and finance.

• Define Node and Cluster Configurations: Specify node configurations and InfiniBand fabric options for clusters from 64 to 1,024+ GPUs, working with infrastructure engineering to keep NCCL (NVIDIA Collective Communications Library) and MPI (Message Passing Interface) pre-configured and performant out of the box. This role owns defining this performance standard.

• Align Partner Roadmaps: Work directly with NVIDIA and ODM partners so Lambda's product plans and our partners' silicon and systems roadmaps land together, not months apart.

• Turn Silicon Into Product: Partner with data center, supply chain, and infrastructure engineering teams to convert silicon roadmaps into reliable, sellable SKUs (stock keeping units) with clear positioning and launch plans.

• Win Adoption: Bring engineers, designers, executives, and customers along with your roadmap through clear writing, honest data, and direct conversation.

• Ship, Measure, Iterate: Launch new hardware products, define the metrics that tell you whether they are working, and iterate on configuration and positioning based on what the data says.

You

• Have 7+ years of product management experience on technical infrastructure, hardware, systems, or platform products; senior candidates should bring 10+ years and ownership of a multi-team or multi-product roadmap

• Turn data and customer signal into a clear decision about what to build next, and can walk through examples where you saw the what and the so what, and determined the now what

• Have a track record of getting engineers, executives, and external partners to adopt a plan because you made them want to, not because you outranked them

• Have shipped products that required coordinating hardware, software, and operations teams against hard external deadlines

• Are fluent in technical conversations with hardware and systems engineers, and comfortable discussing GPU architectures, interconnects, memory, and data center constraints

• Have made hardware, capacity, or fleet investment recommendations that committed significant capital under uncertainty, and can walk through how the decision played out

• Write documents that lead with the conclusion and the evidence, not the background

• Able to define iterative plans that move an organization from the current state towards the desired outcome

Nice to Have

• Have direct experience in GPU or accelerator hardware, or systems and HPC (high-performance computing) product management

• Have worked inside the semiconductor or original equipment manufacturer (OEM)/ODM ecosystem, or directly with NVIDIA or another silicon vendor on roadmap alignment

• Have owned cloud infrastructure capacity planning or fleet economics

• Have hands-on familiarity with distributed training infrastructure, including InfiniBand fabrics and NCCL

• Have run benchmark programs and used the results to drive buy or configure decisions

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.