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Lambda

Cloud-based GPU services for AI training

Executive Communications Manager

PR & CommunicationsConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Have at least 7 years of communications experience, including in-house experience at a hypergrowth start-up.
  • Have built and managed executive communications playbooks for multiple leaders across an organization.
  • Have strong media relationships and a demonstrable track record.
  • Know the artificial intelligence space, particularly AI infrastructure.
  • Be a strong writer with experience ghostwriting for executives across multiple functions.
  • Work effectively with technical and non-technical teams.

Responsibilities

  • Set the external agenda for each member of the leadership team and run the program behind it.
  • Write talking points, keynotes, long-form pieces, social posts, and other communications.
  • Pitch and place executive interviews, profiles, and speaking opportunities.
  • Build relationships with reporters and analysts who cover AI infrastructure.
  • Build program systems, including message frameworks and talk tracks.
  • Manage agency relationships.

About the Company

Lambda

Cloud-based GPU services for AI training

Lambda Labs provides cloud-based GPU services for AI training and inference via its AI Developer Cloud, powered by NVIDIA GH200 Grace Hopper hardware to efficiently train large language models and generative AI. Customers access on-demand or reserved GPUs and are billed by the hour (for example, NVIDIA H100 at about $1.99/hour); it also offers Lambda Echelon, where clients own infrastructure but pay a monthly hosting and support fee, and Lambda Stack, a software suite that helps ML teams install and upgrade tools like PyTorch, TensorFlow, CUDA, cuDNN, and NVIDIA drivers. The company differentiates itself through competitive pricing, available high-end hardware, and an integrated ML software stack that streamlines workflows. Its goal is to enable scalable, affordable AI development and deployment by providing flexible GPU access, reliable hosting, and easy software deployment for teams working with large models.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$9.1B
Headquarters
San Jose, CA
Founded
2012

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