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Lambda

Cloud-based GPU services for AI training

Internal Tools & Data Product Analyst

Business IntelligenceConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Early-career experience in product, business operations, analytics, or technical program management.
  • Comfort working directly with data, spreadsheets, and lightweight tooling, including SQL, no-code platforms, and AI coding assistants.
  • Some exposure to designing a workflow or tool from the end user's point of view, not only from the data behind it.
  • A track record of shipping a tool, process fix, internal script, or similar deliverable rather than only recommending one.
  • Ability to assess end-user experience and distinguish a technically correct dashboard or tool from one people will actually use.
  • Ability to prioritize across a noisy backlog by weighing impact against effort.
  • Comfort using AI-assisted coding tools to ship small things directly.
  • Ability to build cross-functional relationships.
  • Ability to write clear specs, roadmaps, and requirements.

Responsibilities

  • Partner with business stakeholders to define key metrics and support agreement on a single trusted source for each metric.
  • Contribute requirements for converting manually built, inconsistent reporting into live, self-serve dashboards suitable for executives, including how users drill from a summary number into underlying detail.
  • Help prioritize reports or metrics for automation based on how manual, stale, or error-prone they are.
  • Identify manual, spreadsheet-driven work worth automating and help carry the fix through end to end.
  • Scope each fix and help decide whether to build directly using lightweight scripting, no-code tools, or AI-assisted coding, or to assign it to a full engineering build.
  • Write clear, engineering-ready specifications for work handed off to a technical partner.
  • Identify and document where an AI agent or automation could replace manual coordination, and feed those opportunities into the broader automation roadmap.
  • Help collect tool requests, triage them, and prioritize them based on impact versus effort.
  • Help maintain a visible roadmap so stakeholders understand what is coming next and why.
  • Build relationships with supported teams so priorities remain grounded in their needs.

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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