We are building robots that can handle the physical tasks in warehouse fulfilment that have resisted automation for two decades: picking irregular items, handling soft goods, and placing objects precisely into mixed-SKU cartons. We have fifteen robots deployed in three live warehouse environments. They handle over 40,000 picks per day between them. The manipulation ML — grasp planning, object pose estimation, failure detection, and adaptive re-grasp — runs on our robots in real time with a 200ms end-to-end budget. We are not a university lab. We deploy into operational warehouses where downtime has real costs and robot errors have physical consequences. We are looking for a Senior ML Engineer to own the perception and manipulation learning pipeline — from training data collection through to model deployment on the robot edge. The work requires someone who takes both the ML and the systems engineering seriously, because a model that is accurate in simulation and fragile on the factory floor is worthless to us.