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.
