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Research Engineer

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Onsite

Research Engineer

PANTOGRAPH

Research Engineer

Skills

LinuxKubernetes

2 months ago

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Important information


Contract type:

Permanent

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

12 August 2026

What they need


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 a research engineer to help us train increasingly capable models across enormous and diverse datasets.

You'll work across the boundary between research and engineering: implementing new ideas, scaling experiments across large GPU clusters, building the systems that let us iterate quickly, and figuring out why things aren't working. The work spans large-scale model training, multimodal representation learning, reinforcement learning, data processing, evaluation, and the infrastructure required to support all of it.

You might be a good fit if you:

  • Have trained models across large GPU clusters and are comfortable working with Kubernetes
  • Have built or operated complex distributed systems
  • Have worked with multi-terabyte or multi-petabyte datasets
  • Are comfortable with large-scale data processing tools
  • Care deeply about observability and collect enough metrics to understand what every part of a system is doing
  • Are comfortable moving between research code and production-quality systems
  • Like running experiments, getting surprising results, and digging in until you understand why
  • Move quickly and reach for simple approaches before complicated ones

Nice to have:

  • Experience with JAX
  • Experience writing CUDA kernels or otherwise optimizing GPU workloads
  • Low-level Linux or kernel programming experience
  • Experience with large-scale video or multimodal datasets
  • Experience building training or evaluation infrastructure
  • Experience with distributed training
  • Experience deploying models into real-world systems, especially robotics

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.

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