About the job
We are offering a Summer 2026 internship in Robot Learning for students interested in advancing embodied intelligence through large-scale learning, foundation models, and real-world robotic deployment. As a research intern, you will work closely with FieldAI researchers and engineers to explore novel approaches to robot learning and autonomy, with a focus on scalable methods that generalize across tasks and embodiments. This internship is designed for PhD students who want to connect cutting-edge AI research with practical robotics systems. You will have the opportunity to design experiments, develop learning pipelines, and validate ideas on real robotic platforms, contributing directly to FieldAI’s deployed autonomy stack.
Responsibilities
Design experiments;Develop learning pipelines;Validate ideas on real robotic platforms;Develop multi-modal data collection platform for day/night robot navigation data collection;Collect high-quality datasets for reproducible and comparable research and evaluation;Summarize and publish learnings in high-quality robot research conference or journal
Qualifications
Minimum
Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field;Research experience in robot learning, reinforcement learning, imitation learning, or related areas;Strong foundation in machine learning fundamentals and experimental methodology;Ability to work independently while collaborating effectively in a research environment;Strong interest in embodied intelligence and real-world robotics systems
Preferred
Prior experience working with real robot platforms;Familiarity with ROS or ROS 2;Experience with large-scale or distributed training systems;Publications or open-source contributions in robotics or AI;Background in perception, planning, or control for robotics;Interest in bridging foundational research with deployed robotic systems