One Autonomy for All Robots. Field-proven embodied AI software that is finally unlocking the full potential of mobile robots in the real world. Backed by Khosla.
About the role
We are looking for a Research Scientist to advance the state of the art in large-scale learned humanoid manipulation. In this role, you will develop new methods for learned and physically-grounded models, spanning reinforcement-learning, imitation learning, multimodal representation learning, cross-embodiment transfer, and beyond.
What they're looking for
- PhD in Robotics, Computer Science, Machine Learning, Electrical Engineering, Mechanical Engineering, or a closely related field
- A strong research record in robot learning, robotic manipulation, reinforcement learning, imitation learning, multimodal learning, or a related area
- Demonstrated ability to lead research projects from an initial technical question through rigorous experimental validation
- Deep expertise in at least one relevant area, such as foundation models, VLAs, generative policies, reinforcement learning, imitation learning, or multimodal foundation models
- Experience training and evaluating modern deep-learning models using PyTorch
- Strong understanding of robotic manipulation, including relevant aspects of kinematics, dynamics, control, perception, and planning
More about this role
FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.
We are looking for a Research Scientist to advance the state of the art in large-scale learned humanoid manipulation. In this role, you will develop new methods for learned and physically-grounded models, spanning reinforcement-learning, imitation learning, multimodal representation learning, cross-embodiment transfer, and beyond.
Working within FieldAI’s broader humanoid manipulation roadmap, you will formulate new approaches, design rigorous experiments, and validate resulting capabilities on real humanoid robots. You will work closely with research engineers and systems teams to ensure that research...
Browse similar: AI jobs · AI startup jobs · Startup jobs · Boston