Member of Technical Staff, Research Engineer

pantograph.com; San Francisco (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Pantograph in San Francisco is seeking a research engineer to help train increasingly capable models across enormous and diverse datasets. You will work on large GPU clusters, optimize distributed training, and ensure observability. The role blends research and production-quality engineering in a fast-moving, in-person team environment.

Qualifications

• Experience training models on large GPU clusters.
• Comfortable with Kubernetes and distributed systems.
• Experience with multi-terabyte or multi-petabyte datasets.
• Proficiency with large-scale data processing tools.
• Strong emphasis on observability and metrics to understand systems.

Responsibilities

• Train and improve models across enormous and diverse datasets.
• Move between research code and production-quality systems.
• Design and run experiments to understand performance and behavior.
• Architect scalable training/inference infrastructure for robotics applications.

Skills

GPU clusters

Kubernetes

Distributed systems

Large-scale data processing

Observability

Experimentation

Production-quality code

Tools

CUDA

Job description

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 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.