AI Robotics Researcher Intern; Dexterous Manipulation

Position: AI Robotics Researcher Intern (Dexterous Manipulation)
**** JOB DESCRIPTION
****** About NIO
** NIO is a pioneer and a leading company in the premium smart electric vehicle market. Founded in November 2014, NIO’s mission is to shape a joyful lifestyle. NIO aims to build a community starting with smart electric vehicles to share joy and grow together with users.

NIO designs, develops, jointly manufactures and sells premium smart electric vehicles, driving innovations in next-generation technologies in autonomous driving, digital technologies, electric powertrains and batteries. NIO differentiates itself through its continuous technological breakthroughs and innovations, such as its industry-leading battery swapping technologies, Battery as a Service, or BaaS, as well as its proprietary autonomous driving technologies and Autonomous Driving as a Service, or ADaaS.NIO’s

product portfolio consists of the ES8, a six-seater smart electric flagship SUV, the ES7 (or the EL7), a mid-large five-seater smart electric SUV, the ES6, a five-seater all-round smart electric SUV, the EC7, a five-seater smart electric flagship coupe SUV, the EC6, a five-seater smart electric coupe SUV, the ET7, a smart electric flagship sedan, and the ET5, a mid-size smart electric sedan.

About the Position We are looking for an outstanding AI Robotics Research Intern to join the team s role operates at the cutting edge of embodied AI and dexterous manipulation, with a specific focus on utilizing large-scale foundation models and human data-based learning to empower robots with physical world intelligence.

As an intern, you will tackle the fundamental challenges of dexterous manipulation by harvesting human-object interaction data from diverse sources—ranging from unstructured web videos to high-fidelity human glove-collected data. Your work will involve translating these rich human insights into executable robotic behaviors, bridging the gap between human dexterity and machine execution. You will be responsible for deploying these policies on real hardware, to perform complex, contact-rich tasks in real-world environments# # Project Scope
* ** Learning from Human Demonstrations:
** Develop and refine scalable frameworks for the transfer of human-object interaction skills to diverse robotic embodiments.
* ** Large-Scale Data Synthesis:
** Architect autonomous pipelines to process vast amounts of visual data and human glove-collected data, extracting the spatial and contact-rich information necessary for generalist robot training.
* ** Generative
* *** Embodied AI****:
** Implement state-of-the-art generative architectures to synthesize physically grounded, high-fidelity trajectories based on human reference motions.
* ** Unified Policy Training:
** Explore cross-embodiment representations that enable joint training on human and robot data to improve generalization in unstructured environments.
* ** Sim-to-Real Deployment:
** Research and optimize distillation and retargeting techniques to bridge the gap between simulation-trained policies and physical robotic deployment.
* ** Semantic*
* ** Scene*
* ** Understanding:
** Utilize vision-language foundation models to autonomously segment skills and extract task-relevant parameters from complex human activities.# Deliverables (End of Internship)
* A robust pipeline for converting human multi-modal data into actionable robot motor skills.
* A successful sim-to-real validation of a dexterous manipulation policy on a physical humanoid or multi-fingered platform.
* A high-quality technical manuscript or demo suitable for internal review or submission to a top-tier robotics conference.# # Qualifications
* Master’s or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Mechanical/Electrical Engineering, or related fields.
* Strong technical foundation in robot learning and control, including areas such as reinforcement learning, imitation learning, world modeling, or representation learning for agent-environment interactions.
* Practical experience implementing and fine-tuning Generative Models and Transformer architectures.
* Hands-on experience with robotic manipulation systems, particularly involving contact-rich interaction, grasping, or…