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 advances translate into scalable, reliable manipulation and loco-manipulation systems. You will also contribute to FieldAI’s technical direction in robotics foundation models, including how models are architected, trained, evaluated, adapted, and deployed across robotic platforms. This role combines fundamental research with the opportunity to demonstrate meaningful advances on complex real-world robotic systems.