Jobs at UMA

Own the whole-body controller and state estimation for a humanoid robot on real hardware. Responsibilities include designing locomotion and loco-manipulation controllers, floating-base estimation, contact detection, sensor fusion, real-time optimal control, actuator characterization, simulation-to-hardware deployment, model-based and learned policy integration, and diagnostic tooling.

Develop simulation environments for humanoid locomotion, implementing and testing control strategies, and enhancing motion through reinforcement learning and optimization.

This open candidate position invites individuals passionate about Robotics and AI to propose innovative ideas and solutions in a fast-paced startup environment.

Develop and implement learning-based control systems for humanoid robots, using reinforcement learning and other techniques, while optimizing performance and conducting experiments.

As a Research Scientist/Engineer Intern, you will contribute to building learning-based control systems for humanoid robots and work on reinforcement learning and real-world applications while collaborating with the founding team to advance robotics technology.

Lead design and operation of a production-scale data platform for robotics: capture, storage, versioning, high-throughput training pipelines, dataset production from RL/continuous loops, tooling for visualization and debugging, and growth of compute/training infrastructure to keep GPUs fed and enable a continuous data-to-model loop.

Implement and reproduce state-of-the-art world-model baselines, build training/data/evaluation pipelines, run latent-space planning and MPC experiments in simulation and on humanoid robots, and scale and debug distributed GPU training to keep experiments reproducible and logged.

Build and test humanoid robot hardware while integrating mechanical systems and custom electronics, focusing on performance and reliability improvements.

Lead research on world models, planning, and reasoning for humanoid robots. Design and run experiments in simulation and on hardware, own data processing, model training, evaluation, and integration with control stacks, and document and mentor engineers to ship real-world capabilities.

As a Robotic Teleoperator, you will remotely pilot robots during tests, collect data for AI enhancement, monitor robot actions, and collaborate with engineers for improvements.