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AI Robotics Researcher

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: NIO
Full Time position
Listed on 2026-02-16
Job specializations:
  • Engineering
    Robotics, AI Engineer
Salary/Wage Range or Industry Benchmark: 60000 USD Yearly USD 60000.00 YEAR
Job Description & How to Apply Below

NIO is a global smart electric vehicle company founded in November 2014. Dedicated to shaping a sustainable and brighter future together by providing high-performance smart electric vehicles and exceptional user experiences, NIO is the first car company listed on the NYSE, HKEX and SGX.

NIO currently has three major brands under its umbrella: NIO, ONVO and firefly. Ten years into establishment, NIO is now one of the leading companies in the global premium smart electric vehicle market, committed to fostering its own research and development capabilities for core technologies.

As of the end of June 2025, the company had filed for and obtained over 9,900 patents. Additionally, NIO has developed NIO Full Stack, a collection of 12 technology domains. Currently, NIO has R&D centers and manufacturing facilities in over 10 locations, including Shanghai, Hefei, Beijing, Nanjing, San Jose, Munich, Oxford, Budapest, Singapore, and Abu Dhabi. Additionally, it has built a sales and service network across 10 countries and regions, including China, Europe, the Middle East and the Greater Caucasus, serving users in over 350 cities worldwide.

NIO currently offers nine premium smart electric vehicle models under the NIO brand, two smart electric vehicle under the ONVO brand and one small, smart, high-end electric vehicle under firefly brands.

About the Role

We are seeking a talented AI Robotics Researcher to join our next-generation intelligent systems team—pioneering the intersection of embodied AI, dexterous robotic manipulation, and physical world understanding. This role is ideal for PhD students or recent graduates passionate about bridging fundamental AI research with real-world robotic impact—from developing generalizable models for robot perception and control to enabling dexterous robotic hands to manipulate complex objects in unstructured environments.

You will tackle challenges that lie at the heart of embodied intelligence: how robots perceive, reason, and act in the physical world. You’ll work on models that unify visual, tactile, and proprioceptive learning; build world models that enable prediction and generalization; and deploy AI-driven robots that interact safely and effectively in the real world. Your work won’t stay on paper—you’ll see it come to life through physical robots performing complex tasks, making your research tangible, visible, and impactful across warehouses, factories, and mobility environments.

This position offers the rare opportunity to combine cutting‑edge research freedom with practical real‑world deployment, shaping the next wave of intelligent embodied systems.

Responsibilities
  • Conduct original research in embodied AI, robotic manipulation, and world modeling—including perception, planning, and control.
  • Develop and evaluate large-scale multimodal models that integrate vision, language, proprioception, and tactile inputs for real‑world robotic tasks.
  • Create and prototype algorithms for dexterous robotic hands, contact‑rich manipulation, and adaptive task generalization.
  • Explore methods for sim‑to‑real transfer, self‑supervised physical interaction learning, and reinforcement learning in dynamic environments.
  • Collaborate with hardware and systems teams to translate research into real robotic systems—from simulation to physical deployment.
  • Publish and present your work at top‑tier venues (e.g., CoRL, ICRA, RSS, NeurIPS) and contribute to advancing the state of embodied AI globally.
  • Shape the long‑term roadmap of NIO’s embodied intelligence initiative, defining the frontier of AI‑powered robotics in real‑world domains.
Qualifications
  • Master’s or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Mechanical/Electrical Engineering, or related fields.
  • Deep understanding of robot learning, reinforcement learning, imitation learning, world modeling, or differentiable physics simulation.
  • Hands‑on experience with robotic manipulation, grasp planning, tactile sensing, or multi‑sensor fusion.
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, Tensor Flow), and robotics middleware such as ROS
    2.
  • Demonstrated ability to conduct independent research and publish in leading…
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