AI Research Scientist Intern (PhD), Embodied AI

We are seeking an **AI Research Scientist Intern (PhD)** to join us in advancing the frontier of **Embodied AI** for robotics. This role is centered on developing next-generation robot intelligence, with a particular focus on **world models, Vision-Language-Action (VLA) models, post-training, and reinforcement learning**. You will work alongside a team of world-class researchers and engineers on ambitious, real-world problems at the intersection of **foundation models, decision-making, and robotics**. This is an opportunity to help shape core research directions, build cutting-edge systems, and contribute to work with strong potential for **publication at top-tier conferences**. ### **Responsibilities** * Conduct research and develop advanced **Embodied AI** methods for robotic perception, reasoning, and control, with emphasis on: + **World Models** for action-conditioned prediction, planning, and long-horizon decision-making + **Vision-Language-Action (VLA) models** for general-purpose robotic manipulation + **Post-training** methods such as supervised fine-tuning, preference optimization, policy improvement, and online/offline adaptation + **Reinforcement Learning** for improving robustness, generalization, and task performance * Design and execute large-scale experiments to advance robot learning capabilities across challenging manipulation and embodied reasoning tasks. * Collaborate closely with robotics, hardware, and infrastructure teams to bring research ideas into real robotic systems. * Evaluate new methods on real-world and benchmark tasks, and help define rigorous research standards for the team. * Contribute to technical reports, open research discussions, and **publications at leading conferences** where appropriate. ### **Qualifications** * Currently pursuing or recently completed a PhD in Computer Science, Robotics, Machine Learning, or a related field. * Strong research background in **Embodied AI**, **robot learning**, **foundation models**, or a closely related area. * Hands-on experience with one or more of the following: + **World models** + **Vision-Language-Action (VLA) models** + **Post-training / policy fine-tuning** + **Reinforcement learning**, including offline RL, online RL, or RL for control * Strong understanding of modern machine learning architectures, including **transformers**, **diffusion models**, and multimodal learning systems. * Proficiency with deep learning frameworks such as **PyTorch**, **JAX**, or **TensorFlow**. * Strong experimental and problem-solving skills, with the ability to independently drive research ideas from concept to evaluation. * **Requires 5 days/week in-office collaboration with the team.** ### **Preferred Skills** * Experience with robotic manipulation, imitation learning, or large-scale robot policy learning. * Familiarity with **post-training pipelines** for large models, including supervised fine-tuning, preference optimization, or RL-based policy improvement. * Experience with **simulation-to-real transfer**, long-horizon decision-making, or action-conditioned prediction. * Exposure to multimodal learning across **vision, language, action, and proprioception**. * Background in **bimanual manipulation**, **synthetic data generation**, or **3D/spatial reasoning** for robotics. ### **Why Join Us** * Work on challenging, high-impact problems at the frontier of **AI and robotics** * Collaborate with a highly technical, research-driven team * Gain hands-on experience building real systems for **Embodied AI** * Opportunity to contribute to **research publications** and help shape emerging directions in the field * See your work influence both long-term research and practical robotic capabilities