Research Scientist - Physical AI & Robot Foundation Models
LG AI Research · Gangseo, SO, KOR
a month agoImpress employers and recruiters.
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About the Role
Physical Intelligence Lab is researching and developing innovative Robot Foundation Models (RFM) to create world-class Physical AI technology. We are looking for individuals to join us in building next-generation robot intelligence models that enable robots to understand visual information, interpret language instructions, and perform appropriate actions in real-world environments. This involves constructing large-scale robot learning datasets, performing simulation-based learning and validation, and evaluating performance in real robot environments to enhance the generalization capabilities of universal robot intelligence that can robustly handle diverse task conditions and environmental changes.
Responsibilities
- Develop new RFM model architectures and training methodologies.
- Improve RFM pre-training and post-training (SFT, RL) performance.
- Enhance generalization through collection and configuration of robot learning data (Real/Sim/Web) and research on data mixing strategies.
- Analyze the latest research trends in VLA/World Model and integrate/improve internal RFMs.
- Apply research and development results to products and services.
Requirements
- Master's degree in computer vision, machine learning, robotics, or related fields with over 3 years of relevant experience, or a Ph.D. (including expected graduates).
- Experience in research and development related to RFM (VLA, World Model, etc.) or robot learning (Imitation Learning, Reinforcement Learning, etc.).
- Proficiency in model implementation and training using deep learning frameworks such as PyTorch.
Skills
- PyTorch
- VLA
- World Model
- Imitation Learning
- Reinforcement Learning
- Isaac Sim
- MuJoCo
Location
- South Korea
Work Type
- Full-time
Experience Level
- 3+ years of relevant experience
- Ph.D.
Education Level
- Master's degree
- Ph.D.
About the Company
- Physical Intelligence Lab is researching and developing innovative Robot Foundation Models (RFM) to create world-class Physical AI technology.