Member of Technical Staff, Research Engineer

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.