Technical Product Marketing Manager - Public Cloud
Quick Summary
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, 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 San Jose office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.
An ML team spins up an on-demand instance to prototype, outgrows it within a month, and needs a 512-GPU cluster with managed Slurm before their next training run. This role owns how Lambda meets them at every step: how the Public Cloud portfolio is positioned, packaged, launched, and enabled across self-service and sales-assisted motions.
Lambda Cloud is a unified public cloud purpose-built and performance-optimized for AI workloads. The portfolio spans on-demand and reserved GPU instances, 1-Click Clusters, managed Kubernetes and Slurm, and supporting storage, networking, and platform capabilities. It serves customers ranging from AI-native startups and ML teams to enterprises and frontier labs.
We're hiring a technical product marketing manager to own product marketing for the Public Cloud portfolio. You'll define how the portfolio is positioned, packaged, launched, and enabled across self-service and sales-assisted motions, working daily with product management, engineering, sales, solutions engineering, enablement, finance, and marketing. Product management owns product truth. You translate that truth into positioning, use cases, launches, and content that drive adoption and revenue.
This role requires infrastructure depth. You can explain how GPU architecture, interconnect, storage throughput, data movement, orchestration, reliability, and cloud consumption models affect distributed training and inference. You can also communicate those tradeoffs to ML engineers, Enterprise architects, sales teams, and executive buyers.
Responsibilities
~1 min read- →
Requirements
~1 min read7+ years of product marketing, technical marketing, product management, or related experience in cloud infrastructure, IaaS, managed services, or adjacent developer platforms
Demonstrated ownership of a technical product portfolio, including positioning, use-case development, product launches, competitive strategy, field enablement, and adoption
Deep working knowledge of AI infrastructure, with the ability to independently reason about GPU architectures, bare metal and virtualized compute, multi-node cluster topology, InfiniBand and RDMA fabrics, Ethernet networking, storage and data movement, Kubernetes and Slurm, APIs, observability, reliability, and cloud security
Demonstrated ability to produce technical content (benchmarks, whitepapers, architecture guides, datasheets, solution briefs, and technical demos) that withstands review by engineering audiences
Strong written and verbal communication across technical and GTM audiences, from engineers and infrastructure architects to sales leadership and executive buyers
Nice to Have
~1 min readHands-on experience deploying AI or HPC workloads using a cloud console, API, CLI, Kubernetes, or Slurm
Familiarity with CUDA, PyTorch, NCCL, distributed training frameworks, and benchmarking methodologies such as MLPerf
Experience marketing managed Kubernetes, managed Slurm, GPU cloud infrastructure, or MLOps offerings
Previous experience as a product manager, solutions architect, infrastructure engineer, developer advocate, or technical sales engineer
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.
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
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.
Location & Eligibility
Listing Details
- Posted
- September 1, 2026
- First seen
- September 26, 2026
- Last seen
- September 26, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 16%
- Scored at
- September 26, 2026
Signal breakdown
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