Robotics Research Internship, Humanoid Manipulation; Summer | PhD Internship

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 offering a Summer 2026 internship focused on humanoid manipulation for PhD students interested in advancing embodied intelligence on real robotic systems. As a research intern, you will work at the intersection of robotics research and applied engineering, contributing to manipulation capabilities for humanoid robots that directly support FieldAI’s autonomy and robot learning efforts.

You will collaborate closely with Field AI research scientists and engineers to design experiments, develop manipulation systems, and test ideas on real hardware. This internship emphasizes translating research into practical, scalable systems, while also contributing to longer-term efforts around embodiment-agnostic robotics foundation models.

• Advance Humanoid Manipulation Research
• Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.
• Explore loco-manipulation problems that integrate perception, planning, and control.
• Contribute to research projects from early ideas through on-robot experimentation.
• Build Systems That Bridge Research and Deployment
• Translate research concepts into working robotic systems tested on real hardware.
• Develop experimental setups and tooling to support data collection and evaluation.
• Help ensure manipulation systems are robust, reproducible, and field-relevant.
• Contribute to Robotics Foundation Model Development
• Support data collection pipelines used to train robotics foundation models.
• Work with embodiment-agnostic representations to enable transfer across robot platforms.
• Collaborate with researchers to integrate manipulation data into scalable learning frameworks.
• Collaborate Across Disciplines
• Partner with mechanical and electrical engineers on hardware integration and system bring-up.
• Work with