UX Engineer
Google DeepMind
I work on how people control robots. That covers teleoperation interfaces — the systems an operator uses to drive a robot directly — along with the infrastructure those interfaces run on and the data collection pipelines that turn operator sessions into training data.
Teleoperation sits in an unusual place. It is a real-time control problem, a UX problem, and a data problem at once: the same session that lets a person complete a task is also the demonstration a model learns from. Designing for the operator and designing for the dataset are not the same thing, and most of the interesting decisions live in that tension.
This work supports DeepMind's broader robotics effort, including Gemini Robotics — vision-language-action models intended as a general intelligence layer for robots, able to generalize across different hardware and to tasks they were not explicitly trained on, rather than being purpose-built per task.
- Teleoperation interfaces for direct human control of robot hardware.
- Supporting infrastructure and internal tooling around those interfaces.
- Data collection systems that capture operator demonstrations for training.