The Opportunity

About the Team – LG’s Emerging Technology Lab

LG’s Emerging Technology Lab (ETL) is the catalyst for technological innovation within LG’s CTO organization. Based in Silicon Valley and New Jersey, we drive excellence across the CTO organization and LG’s business units by pioneering select emerging technology areas. As a Center of Excellence (CoE), we define and shape key technology domains, setting strategic directions that foster impactful internal and external partnerships and deliver measurable business value.

About the Position – Physical AI Lead

We are seeking an exceptional Physical AI researcher to help define the future of embodied intelligence at LG and shape our research and product roadmaps toward the vision of Zero-Labor Home.

This hybrid role, based at LG's Emerging Tech Lab in Santa Clara, CA, offers a unique opportunity to develop generalist robot intelligence and deploy it at scale in next-generation LG robot platforms. You will work at the frontier of embodied intelligence, leading research that can transition from breakthrough ideas to real-world products at global scale.

You will lead a growing team of Physical AI researchers and work closely with robotics and AI teams across LG to translate cutting-edge research into next-generation intelligent systems.

What You Will Do

• Set the technical direction for LG’s Physical AI team, leading advanced research in multimodal robot foundation models and physical intelligence.
• Lead and manage collaborations with LG HQ and third-party research labs to drive the technical integration of advanced robotics technologies into the LG ecosystem.
• Build and influence a cross-functional Physical AI ecosystem, partnering with LG’s AI, robotics, software, and product teams as well as leading external research partners.
• Define project scope, goals, and deliverables that align cutting-edge research with strategic business objectives.
• Lead fundamental and applied research that advances the scientific and technological frontiers of physical intelligence, with a clear path toward real-world robotic systems.
• Invent and improve paradigms for physical intelligence, including multimodal foundation models (images, video, text, tactile, etc.), world-action models, generalist dexterity, and agentic robot orchestration.

Why This Opportunity Is Unique

• See your research move beyond the lab. Work at the intersection of frontier AI research and large-scale consumer deployment, where breakthroughs can transition rapidly from research into products.
• Maintain a strong research presence while building real products, with support for research ownership, publication, and collaboration with leading universities and AI labs.
• Engage with startups and industry collaborators to co-design hardware-software systems and validate them in real-world applications.
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Required Qualifications

• PhD in Computer Science, Robotics, Machine Learning, or a related technical field, with a strong publication record and 3+ years of industry experience.
• Deep research and engineering expertise in one or more of the following areas:
• Robot foundation models (e.g., VLAs, LBMs, diffusion/flow matching policies for manipulation and locomotion)
• World model training for robot action prediction
• Spatial intelligence (self-supervised visual foundation models, 3D scene reconstruction, embodied scene understanding)
• Multimodal representation learning across vision, language, and touch
• Learning from human demonstrations and self-play
• 1+ years of experience leading technically ambitious research projects in dynamic, fast-moving environments.
• Hands-on experience integrating AI models with real robotic systems, including manipulators and/or mobile robots, and sensors such as RGB and depth cameras, LiDAR, force-torque sensors, and tactile sensors.
• Experience with physics-based simulation platforms (e.g., PyBullet, MuJoCo, Isaac Sim) for large-scale data generation, experimentation, and evaluation.
• Excellent written and verbal communication skills, with the ability to clearly articulate complex technical ideas across research, engineering, and leadership teams.

Please Note: the salary range provided is dependent on the experience and level of candidate hired.

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