AI Research Scientist, Robotics

The ideal Research Scientist candidate will use their skills in system design and modeling and possess knowledge of a wide variety of components and technologies. These roles will require research and problem-solving skills, as well as fabrication and prototyping to design, develop, and construct novel prototypes and architectures. These roles will work in a focused incubation team and collaborate with a large and wide-ranging set of scientists and engineers in the greater organization.

Perform fundamental and applied research to push the scientific and technological frontiers of embodied artificial intelligence Invent/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 functionalities needed for the next generation of AI Conduct research towards long-term product goals while identifying intermediate milestones Plan and execute novel research based on long-term objectives of the organization

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently has or is in the process of obtaining a 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, motion planning, embodied AI, human-robot interaction, sim-to-real transfer, learning from demonstration, reinforcement learning, dexterous manipulation, digital agents, vision language models, computer vision, egocentric perception, and/or LLMs Experience in relevant robotics related research areas, such as: VLM, 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 solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward Experience working with robot simulations and real-world hardware 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 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 manipulating and analyzing complex, large scale, high-dimensionality data from varying sources 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) Experience with deep learning frameworks (such as PyTorch, Tensorflow) and Python