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
- 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.
- 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.
- 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 multi-sensor perception (e.g., tactile, force/torque, proprioception).
- Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow), with experience using robotics middleware or simulation tools (e.g., ROS/ROS2, MuJoCo, Isaac Sim, PyBullet).
- Demonstrated ability to implement, experiment, and iterate on research ideas, including evaluating methods through empirical results on simulated or physical robotic systems.
- Strong analytical and system-building skills, with the ability to work across simulation, learning, perception, control, and real robot deployment as part of a larger technical team.
- Ph.D. (or Ph.D. candidate expecting graduation within 6–12 months).
- Prior experience with dexterous manipulation, multi-finger robotic hands, in-hand manipulation, or grasp optimization beyond parallel-jaw grasping.
- Experience deploying learning-based policies on real robotic hardware, including exposure to sim-to-real transfer challenges such as contact mismatch, compliance, sensing noise, or latency.
- Familiarity with contact modeling, tactile sensing, force/torque feedback, or low-level control interfaces for manipulation.
- Background in 3D perception, geometric representations, or learned representations relevant to physical interaction.
- Experience with reinforcement learning in continuous control, model-based methods, or real-time policy execution.
- A strong interest in building robust, real-world robotic systems, and motivation to see research ideas validated through physical experiments rather than simulation alone.
- Track record of publications in top AI or robotics conferences (CoRL, ICRA, IROS, RSS, NeurIPS, CVPR, ICML).
Compensation:
The US base salary range for this full-time position is $38.00 - $46.00.Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Please note that the compensation details listed in US role postings reflect the base salary only. It does not include discretionary bonus, equity, or benefits.
NIO Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NIO and has not been reviewed or approved by NIO.
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Fair & Transparent Compensation — Pay and benefits are rated highly in at least one cited source, and the provided figures position total compensation as competitive within tech/EV roles. The package appears stronger for senior and specialized roles given the upper-end salary ranges shown.
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Equity Value & Accessibility — A stock ownership plan is described as covering all employees, indicating broad access to equity participation. This design links employee rewards to company performance through shared ownership.
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Wellbeing & Lifestyle Benefits — Workplace perks include flexible hours, catered lunch, unlimited PTO in older accounts, and lifestyle supports such as free snacks/drinks and fitness stipends. These benefits add day-to-day value beyond base pay.
NIO Insights
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What We Do
NIO’s mission is to shape a joyful lifestyle by offering premium smart electric vehicles and providing the best user experience. NIO was founded in November 2014 as a global electric vehicle company. The company has over 7,000 employees working across world-class research and development, design and manufacturing centers in Shanghai, Beijing, San Jose, Munich, London and six other locations. In 2015, NIO was the title sponsor for the Drivers’ Championship winning team during the inaugural ABB FIA Formula E season. In 2016, NIO unveiled one of the fastest electric cars in the world, the EP9. The EP9 set the lap record for an electric vehicle at the Nürburgring Nordschleife and three other world-renowned tracks. In 2017, NIO unveiled its vision car EVE and announced that the NIO EP9 set a new world speed record for an autonomous vehicle at the Circuit of the Americas. NIO officially began deliveries of the ES8, the high-performance electric flagship SUV, on June 28, 2018. NIO was listed on the New York Stock Exchange on September 12, 2018. NIO officially launched the high-performance long-range electric SUV, NIO ES6, at NIO Day on December 15, 2018. On May 28, 2019, the first production model ES6 rolled off the line at the JAC NIO Advanced Manufacturing Center. NIO officially began deliveries of the ES6 on June 18, 2019. NIO officially launched the EC6, a 5-seater smart premium electric coupe SUV, in December 2019 and began deliveries of the EC6 on September 2020. On January 9, 2021, NIO ET7, the smart electric flagship sedan and NIO’s first autonomous driving model, was officially launched.
