You will sit with customers' ML engineers to understand what they are actually training and serving — GPU type, cluster requirements, networking, utilization and performance objectives — then design the right architecture on Prime infrastructure, run the POC against their baseline and the competitive alternatives, and turn latency, throughput, utilization, and cost results into a technical business case that holds up under scrutiny. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models.