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About the Role
Pantograph is training general models that start by watching internet-scale video and end up on robots. This role requires someone who can architect and own the entire infrastructure pipeline behind a fleet of thousands of robots with embedded GPUs, communicating over wifi to inference clusters, streaming tens of petabytes of video to training clusters, with new model weights deployed every few minutes — all operating within strict real-time latency budgets. You'll touch networking, storage, databases, embedded software, deployment systems, and GPU optimization — and you'll own the architecture decisions that tie them together.
Responsibilities
- Architect and own the entire infrastructure pipeline behind the robot fleet.
- Optimize the system end-to-end, touching networking, storage, databases, embedded software, deployment systems, and GPU optimization.
- Make architecture decisions that tie together various system components.
Requirements
- Designed and operated large-scale distributed systems from scratch.
- Managed fleets of hundreds or thousands of computers.
- Deep experience with GPU performance optimization, including writing custom CUDA kernels.
- Worked on real-time embedded systems or robotics infrastructure.
- Built petabyte-scale storage and database systems.
- Experience with high-performance networking and video encoding pipelines.
Skills
- Distributed systems architecture
- Fleet management
- GPU performance optimization
- CUDA kernel development
- Real-time embedded systems
- Robotics infrastructure
- Petabyte-scale storage
- Database systems
- High-performance networking
- Video encoding pipelines
- Rust
- Low-level performance optimization
Location
- San Francisco
Work Type
- In person
- Small team
Experience Level
- Senior
About the Company
- Pantograph is training general models that start by watching internet-scale video and end up on robots.
- We think the path to capable robots runs through general intelligence rather than narrow, robot-specific skills.
- We're scaling simple methods across video games, real-world video, and our own fleet of affordable, durable robots.
- We are a small, fast-moving team working together in person in San Francisco.
- We care much more about what you've built than any specific credential.