Member of Technical Staff, Infrastructure & Systems Lead

pantograph.com; San Francisco (CA); Presencial; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

Pantograph is building general models that start by watching internet-scale video and end up on robots with embedded GPUs. We’re seeking an architect to own the entire infrastructure pipeline behind the fleet, including networking, storage, databases, and deployment systems, all within strict real-time latency budgets.

You’ll design and operate large-scale distributed systems, manage fleets of hundreds or thousands of machines, optimize GPU performance, and ensure seamless data movement from

Formación

• Experience designing and operating large-scale distributed systems.
• Ability to manage fleets of hundreds to thousands of computers.
• Deep GPU performance optimization, including custom CUDA kernels.
• Experience with real-time embedded systems or robotics infrastructure.
• Experience building petabyte-scale storage and database systems.
• Strong networking and video encoding pipeline knowledge.

Responsabilidades

• Own end-to-end architecture decisions tying networking, storage, databases, and deployment.
• Optimize the entire infrastructure pipeline for real-time latency budgets.
• Work in a hands-on role in a small, fast-moving San Francisco team.

Conocimientos

Distributed systems

Fleet management

GPU optimization

Real-time embedded

Petabyte storage

Networking & video pipelines

Descripción del empleo

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're looking for someone to architect and own the entire infrastructure pipeline behind that fleet: 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.

This role requires someone who can hold an entire system in their head and optimize it end-to-end. You'll touch networking, storage, databases, embedded software, deployment systems, and GPU optimization — and you'll own the architecture decisions that tie them together.

You might be a good fit if you have:

• 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

Nice to have:

• Rust and low-level performance optimization experience
• Experience taking infrastructure from prototype to production in a small team

We care much more about what you've built than any specific credential. We're a small, fast-moving team working together in person in San Francisco. If you're excited about architecting novel systems at unprecedented scale, we'd love to talk.