Researcher(Embodied AI)
Air Liquide is hiring a Researcher(Embodied AI) in Shanghai, China. Level rates it ; you can apply on Air Liquide.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include PyTorch and computer vision.
- Level lists 1,000+ other open roles at Air Liquide.
AI in this role
液化空气集团早在1916年就进入中国,70年代开始向中国提供空分设备,经过多年的稳步发展,目前在中国设有近120家工厂,遍布40多个城市,拥有约5000名员工。集团在华主要经营范围包括工业及医用气体的运营,家庭健康服务,工程与制造业务,以及全球市场与技术和上海创新园从事的创新业务。公司业务已覆盖中国主要的沿海工业区域,并继续向中部、南部和西部地区拓展。
液化空气通过创造卓越绩效和履行责任追求盈利性增长和长期可持续发展,并保持在中国的行业领先地位。依托于集团的长期战略与全球资源,公司聚焦能源、环境、高科技和健康等领域,以迎接挑战并创造新的市场机遇。凭借专业团队的全力支持,公司致力于为客户提供可信赖的服务与高附加值解决方案,同时履行企业社会责任。
您将如何贡献和成长?
Focusing on the business needs of Air Liquide in the context of our customer-centric transformation, the researcher will be responsible to:
- Collaborate with business entities to define the problem and business requirements, translate them into functional design specifications, and develop solutions. Identify, evaluate and select industrial or academic partners as needed.
- Develop and optimize core algorithms for Embodied AI, including:
- Multimodal Perception: Fuse sensory data from vision (cameras), LiDAR, and tactile sensors to enable robots to "see" and "comprehend" complex industrial settings.
- Autonomous Planning & Decision-making: Research the application of AI models (e.g., LLMs/VLMs, Reinforcement Learning, world models) for high-level task planning, reasoning, and dynamic decision-making.
- Learning & Control: Develop efficient robotic control policies, particularly through Reinforcement Learning (RL), Imitation Learning (IL), and Sim-to-Real transfer, allowing robots to rapidly acquire new skills (e.g., dexterous manipulation, obstacle-avoiding navigation).
- Lead the end-to-end deployment of Embodied AI algorithms on industrial robots and mobile manipulators (AMR + robotic arms), overcoming the technical challenges of Sim-to-Real transfer in complex, real-world industrial environments.
- Participate in the joint debugging of robotic hardware and software systems. Collaborate closely with internal engineering and process teams to drive the production/laboratory deployment of tasks such as smart grasping, autonomous navigation, and complex equipment manipulation.
- Train team members on the details of the implemented methodology, thus ensuring sustainability of the solution for Air Liquide.
- Support knowledge transfer within Air Liquide. Publish research in internal R&D reports, at conferences and potentially in peer-reviewed journals.
- Maintain keen insights into advancements across Physical/Embodied AI, robotics, and LLM/VLM applications, strategically evaluating and introducing new technologies to drive technical choices and innovation.
您是合适的人选么?
- Master’s degree or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Automation, or a related engineering discipline. Proven experience in independent and interdisciplinary research is highly preferred.
- Deep project experience in Computer Vision (CV) (e.g., object detection, segmentation) and Reinforcement Learning (RL).
- Solid foundation in machine learning; expert proficiency in Python and at least one mainstream deep learning framework (PyTorch preferred).
- Solid understanding of robot kinematics, dynamics, SLAM (mapping and localization), and path planning.
- Proficiency in ROS (ROS/ROS2) with rich, hands-on development experience.
- Proven track record of deploying and debugging algorithms on at least one type of physical robot (e.g., quadrupedal robots, UAVs, mobile robots/AGVs, or robotic arms).
- Outstanding rapid-learning agility and the ability to navigate open-ended, ambiguous technical challenges.
- Excellent communication and interpersonal skills (written and oral). Must be comfortable to work in English on a daily basis and in a multi-disciplinary and international team. Knowledge of French is of benefit.
关于液化空气集团
液化空气集团 —— 全球工业与健康领域气体、技术和服务的领导者之一,业务遍及78个国家/地区,员工约64,500
人,为380多万名客户与患者提供服务。氧气、氮气和氢气是生命、物质及能源不可或缺的小分子。它们象征着液化空气的科学疆域,自集团1902年成立以来,始终位于其业务的核心。
多样化造就了我们的业绩
在液化空气,我们致力于建立一个多元化和包容性的工作场所,拥抱来自全球的员工、客户、患者、社区利益相关者和文化的多样性。
我们欢迎并考虑所有合格申请人的申请,无论他们的背景如何。我们坚信,多元化的组织为人们提供了展示个人和集体才能的机会,它有助于培养我们的创新能力,通过践行我们的基本原则、为我们的成功而努力并在不断变化的世界中创造一个有吸引力的环境。
How we rate this
Researcher(Embodied AI) at Air Liquide rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Walk me through how you've used PyTorch in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Computer vision and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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