# Research Engineer at Pantograph

> Onsite · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Apantograph%3Ad4342f78-a21f-47ea-9678-9dcc13e63f93 (read 2026-11-11).

## Facts (observed)

- Company: [Pantograph](https://alderhq.app/companies/pantograph)
- Location text: San Francisco
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Francisco")
- Posted: 2026-08-11 (91 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/pantograph/d4342f78-a21f-47ea-9678-9dcc13e63f93
- Skills listed (inferred): Kubernetes, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (SF Bay Area, n 544): p25 $200k, median $249k, p75 $300k

## Description (the employer's text)

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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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Apantograph%3Ad4342f78-a21f-47ea-9678-9dcc13e63f93 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.