Technical Product Marketing Manager - Public Cloud

Posted 2 Days Ago
Be an Early Applicant
2 Locations
Hybrid
180K-240K Annually
Senior level
Software
The Role
Own product marketing for Lambda’s Public Cloud portfolio, including positioning, use cases, launches, technical content, competitive strategy, sales enablement, and adoption. Translate AI infrastructure capabilities into compelling messaging for ML engineers, enterprise architects, sales teams, and executives. Partner with product, engineering, sales, finance, and marketing to launch GPU instances, clusters, managed Kubernetes, Slurm, storage, networking, and platform services.
Summary Generated by Built In

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.

What You’ll Do

  • Own Public Cloud product marketing. Define and maintain positioning, messaging, audience segmentation, and the use-case library across the portfolio. Serve as the primary product marketing partner to the Public Cloud business unit, working with product management on roadmap context, packaging, and launch planning.

  • Build use cases and the portfolio GTM architecture. Translate training, fine-tuning, inference, and proof-of-concept workloads into documented, sellable use cases mapped to segment and infrastructure requirements. Establish how customers progress from on-demand evaluation to 1-Click Clusters and managed services. Clarify which offering fits each workload, segment, operational model, cluster size, and commercial commitment.

  • Execute product launches. Own launch execution for new product features, instance types, APIs, and managed services. Partner with product management and engineering from roadmap planning through general availability, including launch, audience definition, positioning, technical validation, content, field readiness, and post-launch analysis.

  • Create product-focused technical content. Produce messaging and positioning, solution briefs, datasheets, benchmark narratives, technical blogs, reference architectures, API and CLI walkthroughs, and use cases. Validate every technical claim with Product Management and Engineering.

  • Support sales and solutions engineering. Build discovery frameworks, qualification guidance, pitch materials, proposal content, battlecards, technical training, and competitive displacement narratives. Support active opportunities with workload- and segment-specific positioning.

  • Enable the broader marketing organization. Equip demand generation, growth, content, events, web, communications, and customer marketing with approved messaging, use cases, audience guidance, technical proof points, and launch materials. Review downstream content for consistency and technical accuracy.

You

  • 7+ 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

  • Hands-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

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.

Skills Required

  • 7+ years of experience in product marketing, technical marketing, product management, or a related field within cloud infrastructure, IaaS, managed services, or developer platforms
  • Experience owning a technical product portfolio, including positioning, use-case development, product launches, competitive strategy, field enablement, and adoption
  • Deep working knowledge of AI infrastructure, including GPU architectures, bare-metal and virtualized compute, multi-node cluster topology, InfiniBand, RDMA, Ethernet networking, storage, data movement, Kubernetes, Slurm, APIs, observability, reliability, and cloud security
  • Ability to produce technical content such as benchmarks, whitepapers, architecture guides, datasheets, solution briefs, and technical demonstrations suitable for engineering audiences
  • Strong written and verbal communication across engineers, infrastructure architects, sales leadership, and executive buyers
  • Hands-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 MLPerf benchmarking methodologies
  • 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

Lambda Compensation & Benefits Highlights

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

  • Fair & Transparent Compensation Pay is considered competitive for an AI infrastructure company, with posted ranges and observed offers indicating strong packages for senior technical roles. Compensation is often characterized as competitive or top‑shelf, aligning with market expectations.
  • Healthcare Strength Health, dental, and vision coverage are characterized as strong, with broad‑network plans noted and positive experiences highlighted. This foundation supports overall satisfaction with core insurance benefits.
  • Leave & Time Off Breadth Flexible or unlimited PTO is described as actually used, complemented by paid holidays and sick time. Generous parental leave examples further expand the time‑off offering.

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The Company
HQ: San Francisco, CA
106 Employees
Year Founded: 2012

What We Do

Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.

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