Applied Physical AI Researcher

We empower our people to stay resilient and relevant in a constantly changing world. We’re looking for people who are always searching for creative ways to grow and learn. People who want to make a real impact, now and in the future. Does that sound like you? Then it seems

like you’d make a great addition to our vibrant international team.

For our Autonomous Factory team, we are looking for an Applied Physical AI Researcher pioneering next generation of embodied AI, applying and integrating multimodal foundation models and robot learning architectures into real-world industrial applications.

You’ll make an impact by

• Translating the latest Physical AI research results into real industrial applications, including replicating experimental setups, collecting data, training models, and evaluating performance.
• Analyzing current Physical AI models and pipelines to identify improvement opportunities and close the gap between lab scenarios and real industrial use cases.
• Defining research directions, technical blueprints, and practical research plans for Industrial Physical AI.
• Tackling complex challenges through first-principles thinking, creative problem-solving, innovative ideas, and fast hands-on execution.

Required qualification

• PhD or Master’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, or a closely related field.
• Solid understanding of modern neural network architectures and generative AI technologies, such as Transformers, LLMs, VLMs, VLAs, WAMs, CNNs, and diffusion-based models.
• Experience in data preparation, preprocessing, fine-tuning, and inference optimization for modern LLMs, VLMs, VLAs, or related models.
• Strong programming skills in Python and experience with PyTorch and/or TensorFlow.
• Strong scientific, systematic, and first-principles thinking, with openness to creative experimentation and continuous improvement of state-of-the-art performance.
• Proficient English communication skills, both written and spoken.

Preferred qualification

• Hands-on experience in robotic data collection, data curation, dataset management, model fine-tuning, and inference for VLA or WAM applications.
• Experience developing modern agentic AI systems using frameworks such as LangGraph, LlamaIndex, or similar tools.
• Familiarity with prompt engineering.
• Familiarity with egocentric perception or learning methods, such as first-person vision, egocentric data transformation, action-conditioned representations, or sequential decision-making based on egocentric data.

You’ll benefit from

• Diverse and inclusive culture, doing the work you like with people who appreciate it
• Systematic career development platform, various training courses, and online learning resources for you to help you tailor your growth path based on your strengths
• 15 days + annual leaves, with additional benefits such as Christmas leave
• Generous benefits package, long-term care corporate annuity plan, flexible allocation of commercial insurance, employee stock sharing matching plan for mutual growth, etc.