Research Scientist
We're building robots that learn through exploration in the real world. We're looking for research scientists with strong foundations in reinforcement learning, multimodal representation learning, or large-scale model training.
Qualifications:
- You’ve worked on one of:
- Self-supervised, goal-conditioned, or unsupervised RL
- Large-scale pretraining (language, multimodal, image, or video)
- RL post-training, reasoning, or tool use
- Robotics models, especially methods that involve large-scale pretraining
- Learning methods for low-level motor control
- You’ve worked on large GPU clusters, and are comfortable working with Kubernetes
- You believe that research and engineering are two sides of the same coin
- You strive to find simple, expressive metrics, and to measure them accurately
- You value scientific integrity, and seek to understand the true effect of different interventions
Nice to have:
- Experience with JAX
- A strong proof-based math background, for example:
- Measure-theoretic probability theory
- Stochastic processes
- Optimization theory
We care much more about what you can do than any specific credential. We're interested in published work or lab experience, but equally in strong open-source contributions or personal projects.
We're a small fast-moving team working together in person, in San Francisco. If you're excited about getting robots to learn from the real world, we'd love to talk. To apply: send an email to hiring@pantograph.com with "Research Scientist" in the subject line, and include a CV and a description of your research interests or what excites you about this area.