About the role
Join Us, and Ship Robots
Weave was founded to build the robots we’d want to have in our own home. We believe the next generation of robotics will transform everyday life by enabling people to do more and to reclaim time to spend on what’s important.
We also believe robots are in a sense like any other product: to matter, they have to ship. Our robots are already operating in real homes and businesses, giving us the opportunity to rapidly improve from real-world experience. With a growing team, strong customer demand, and capital for expansion, we’re entering an exciting stage of growth—and we’re looking for people with exceptional talent and standards to help bring home robotics to millions of households.
The Role
Cloud inference, teleoperation, and the companion app all run on infrastructure you'll own. As a Cloud Infrastructure Engineer, you'll build the networking stack that connects robots to GPUs, teleoperators, and customers’ companion apps. You’ll design and implement protocols that keep those connections working on imperfect home networks, and the backend that manages a growing fleet across many customers.
The core problems are real-time: routing a robot to available GPU capacity with latency low enough for closed-loop inference, keeping teleoperation streams stable through jitter and packet loss, and degrading gracefully when the network does. What you build directly sets how responsive every robot in the fleet feels day to day.
Responsibilities
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Build our distributed infra: Design backend services that coordinate robots, cloud compute, teleoperators, and customer applications across unreliable networks and partial failures. Build for fault tolerance, idempotency, consistency, scalability, and graceful degradation as the fleet grows.
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Serve cloud inference: Build low-latency serving infrastructure for models robots call mid-task, including connection management, GPU scheduling and utilization, autoscaling, load balancing, and graceful degradation when connectivity or compute capacity is constrained.
