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Embodied AI Algorithm Engineer/Expert (Embodied Foundation Models)
Beijing
Full-time
Multimodal / Embodied AI foundation models
Relevant background
You will be responsible
- Design and implementation of a Vision-Language-Action (VLA) model for robot decision-making and control
- Build multimodal data and training processes to improve the model's generalization ability in real tasks
- Promote the implementation of the model from offline training to deployment on real robots
- Continuously optimize model performance and inference efficiency, supporting system-level integration
We hope you have
- Background in computer science / artificial intelligence and related fields
- Solid foundation in deep learning, with experience in multimodal or foundation models
- Familiar with Python, familiar with PyTorch / JAX
- Familiar with the training and use of mainstream visual language models (Qwen, etc.) or embodied models (π0, RT, etc.)
Preferred Qualifications
- Has multimodal (vision-language-action) experience related to robots
- Experience in large-scale data training or data engineering
- Experience in model compression / acceleration / deployment
- Experience with top conference papers or open source projects
Our way of working
- Emphasize real closed-loop: algorithms should not only be effective in simulation, but also run stably on real robots.
- Strong engineering orientation: connect the full chain from data → model → deployment, rather than just optimizing a single algorithm.
- Rapid iteration: Move frequently between simulation and physical robots to validate and refine solutions quickly.
- Strong collaboration: algorithms, hardware, and systems closely work together to solve complex embodied problems.
Interested in This Role?
Submit your application below and our team will review your resume shortly.