Cloud AI development platform for training and serving models on GPUs
Lightning AI runs a browser-based AI development platform for coding, GPU training and model serving, built on PyTorch Lightning, CUDA, NCCL and Kubernetes across AWS, Azure and GCP. The hiring mix is senior-heavy and engineering-led, but finance and ops hiring plus a move away from NetSuite point to back-office systems being rebuilt to keep pace with platform growth.
Lightning AI offers a cloud workspace where developers and data scientists write code, prototype, train models on GPUs and deploy them without local setup. The platform supports persistent environments, multi-node scaling, sweeps and jobs, and ties into the company's open-source tooling around PyTorch Lightning. Headquartered in New York, the privately held company has 51–200 employees and hires across the United States, Canada, the United Kingdom and the Philippines. Its stack spans multi-cloud infrastructure, NVIDIA GPUs and TPUs, with HubSpot and Salesforce supporting go-to-market.
Lightning AI uses PyTorch, PyTorch Lightning, CUDA and NCCL on NVIDIA GPUs and TPUs, with Kubernetes, Docker, Terraform and Ceph across AWS, Azure and GCP, plus Python, Go and React.
Yes. Engineering is the largest hiring area, skewed toward senior roles, with additional openings in ops, finance, sales, support and security across the US, Canada, UK and Philippines.
Job posts point to provisioning automation, RESTful resource-management APIs, scaling platform APIs, large-scale training and inference optimization, observability and a microservices-based core architecture.
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Lightning AI's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
