Infrastructure & Systems Lead

PANTOGRAPH INC
San Francisco, CA, United States
about 2 months ago
Apply on www.indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Nvidia CUDA Databases Distributed Systems Performance Tuning Video Encoding

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

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.

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’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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · World Congress 2026 Europe

2:23 min

Evaluating video encoding formats for faster decoding

Magne Johansen Magne Johansen · Europe 2026 Virtual

6:21 min

Previewing upcoming hardware acceleration capabilities for Python environments

Chris Heilmann +2 · LIVE

3:04 min

Database evolution and the funding behind vector databases

Erik Bamberg · LIVE

1:37 min

Accelerating compute with focused developer tools

Julia Koch Julia Koch +1 · World Congress 2026 Europe

3:30 min

Transitioning from CUDA software architect to user

Stephen Jones · Coffee With Developers

Videos

See all

Related articles

See all