GPU Cloud for AI — On-Demand NVIDIA GPUs for Training & Inference
The consensus on Lambda: Choose Lambda if you want to build the GPU cloud that powers AI research — but be aware that management style and company politics are common complaints.
Founded in 2017 by Stephen Balaban, Lambda is building the GPU cloud that powers the AI revolution. The company provides on-demand NVIDIA H100 and H200 GPUs for training, fine-tuning, and inference — alongside Lambda Stack (deep learning software) and custom workstations. Backed by NVIDIA and ARK Invest with $2.3B in funding, Lambda has grown to ~$760M ARR and a $4B+ valuation. The culture is engineering-driven and infrastructure-focused: the team ships critical compute infrastructure that AI researchers and companies depend on daily. Engineers here solve hard systems problems at the intersection of hardware, networking, and distributed computing.
Lambda GPU Cloud provides on-demand NVIDIA H100 and H200 clusters for AI training, fine-tuning, and inference. Engineers work on orchestration, networking, and bare-metal provisioning at scale. Explore Lambda Cloud →
Lambda Stack is the one-line install for deep learning frameworks — PyTorch, TensorFlow, CUDA, and cuDNN on Ubuntu. Used by thousands of researchers and teams to set up GPU workstations and servers.
~500 employees across San Jose, Austin, and remote. Engineering teams are organized around cloud platform, networking, hardware, and developer tools. The NVIDIA partnership shapes much of the technical roadmap.
Explore open roles at Lambda below.