en.Wedoany.com Reported - On June 29, NVIDIA Corporation announced recruitment for its robotics team, opening positions across four core directions: embodied intelligence, simulation, deployment, and solution architecture. Recruitment needs are set in Beijing, Shanghai, and Shenzhen, China. These positions cover humanoid robot hardware solutions, perception systems, motion control AI algorithms, robot learning platforms, real-world deployment, and industry solutions, indicating NVIDIA's expansion of robotics R&D and industrial application support capabilities locally in China.
The embodied intelligence team will focus on advancing technologies such as dexterous manipulation, wearable sensor-based human body modeling, whole-body mobile manipulation, and whole-body control. These positions target next-generation general-purpose robot systems, emphasizing full-stack capabilities from perception and decision-making to execution, integrating physical AI, robot hardware, control algorithms, and simulation platforms into a single R&D pipeline.
The simulation team is responsible for building robot training infrastructure. NVIDIA's platforms, including Isaac Sim, Isaac Lab, and Omniverse, have become essential tools for robot developers to train, test, and validate algorithms. Since trial-and-error in real-world scenarios is costly, simulation platforms can pre-construct physical environments, sensor inputs, task flows, and anomaly situations, allowing robots to complete extensive training in virtual spaces before transferring to applications in factories, warehouses, services, and humanoid robots. Opening simulation-related positions in China indicates NVIDIA's desire to deepen local developers' and industry clients' utilization of the robot training toolchain.
The deployment team focuses on the real-world implementation of humanoid robots and embodied intelligence algorithms. When robots transition from simulation to the real world, they encounter issues such as sensor noise, variations in ground friction, lighting changes, object occlusion, mechanical errors, and task interruptions. Algorithms require real-world debugging, performance optimization, and stability validation. The increase in deployment positions means NVIDIA is pushing its robot software stack from platform capabilities to client sites, helping enterprises implement perception, planning, control, and edge computing capabilities on specific devices.
The solution architecture team handles industry adoption tasks, serving clients in industrial, service, and intelligent automation scenarios. As embodied intelligence enters the enterprise sector, simply providing chips or development kits is no longer sufficient. Clients need complete solutions, including computing platforms, simulation environments, robot models, deployment tools, data loops, and application adaptation. Beijing, Shanghai, and Shenzhen, China, are hubs for robot OEMs, automotive and electronics manufacturing clients, AI algorithm teams, supply chain resources, and industrial application scenarios. NVIDIA's expansion in these three cities helps it stay close to China's robot industry chain and application clients.
NVIDIA has recently been intensifying its "Physical AI" narrative. CEO Jensen Huang, at the shareholder meeting, identified Physical AI as the next wave of growth, stating that robots, cars, and smart factories will become intelligent agents in the real world, with capabilities for perception, reasoning, planning, and autonomous action. During his keynote at the Consumer Electronics Show in January this year, Huang repeatedly mentioned Physical AI, linking robot systems with AI computing platforms, simulation tools, and edge deployment capabilities. This recruitment across three cities in China is a concrete move by NVIDIA to extend its Physical AI strategy into robot R&D, simulation infrastructure, and industrial applications.
China's embodied intelligence and humanoid robot industry is rapidly heating up. OEMs, component suppliers, AI model companies, industrial clients, and capital markets are all accelerating their entry into this track. By opening multiple positions for its robotics team in China, NVIDIA will further strengthen its involvement in robot development platforms, simulation training, edge computing, and industry solutions. For China's robot industry chain, the signal from such recruitment is that general-purpose robot systems are transitioning from concept demonstrations to platform tools, engineering deployment, and collaboration with industry clients.
