Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, robotics, and embodied AI, particularly including areas such as transfer learning, learning from demonstration, reinforcement learning, action-conditioned world models, perception, representation learning, robot control, navigation, mobile manipulation, dexterous manipulation, and vision-language models. You should have a keen interest in producing new, open science to make embodied agents more intelligent.
Responsibilities
Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence
• Invent and improve novel data-driven paradigms for robotics, leveraging a variety of modalities (images, video, text, audio, tactile, etc.)
• Investigate paradigms that can deliver a spectrum of embodied behaviors - from simulated characters to real robots, and from short-horizon, low-level to long-horizon, high-level intelligence
• Develop algorithms based on state-of-the-art machine learning and neural network methodologies
• Define, build, and benchmark new capabilities needed for the next generation of AI
• Conduct research towards long-term research goals while identifying intermediate milestones
• Lead, plan, and execute novel research based on long-term objectives of the organization
Minimum Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• PhD degree in the field of Artificial Intelligence, Robotics, Computer Vision, Machine Learning, Language, a related field, or equivalent practical experience
• Experience with any of the following research areas: robotics, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning, dexterous manipulation, digital agents, vision language models, egocentric perception, and/or Large Language Models
• Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during the employment
Preferred Qualifications
• Experience working and communicating cross-functionally in a team environment
• 2+ years of industry experience in relevant robotics-related research areas, such as: robot learning, reinforcement learning, imitation learning, action-conditioned world models, task and motion planning, sim-to-real transfer robotic control, manipulation, navigation, or generally embodied AI
• Experience with robotics frameworks like ROS, along with experience working with robot simulations and real-world hardware
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops, journals or conferences in Machine Learning (NeurIPS, ICML, ICLR), Robotics (ICRA, IROS, RSS, CoRL), Computer Vision (CVPR, ICCV, ECCV)
• Experience with deep learning frameworks (such as PyTorch, TensorFlow) and Python
• Experience building systems based on machine learning and/or deep learning methods
• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g., GitHub)
