Tasks:
- * Build data training and evaluation pipelines
- * Build multimodal understanding and action-generation algorithms
- * Debug and test algorithms on physical robots
- * Deploy models on edge devices
- * Develop humanoid robot embodied foundation models
- * Develop motion control and cross-embodiment action transfer
- * Develop tactile perception and dexterous manipulation algorithms
- * Integrate robot systems and validate product delivery
- * Manage model versions and regression testing
- * Optimize model quantization and inference
- * Train models using human, robot, and simulation data
Perks/Benefits:
Skills/Tech stack required:
[C++] [Deep learning] [Dexterous Manipulation] [Edge Deployment] [Experimental Design] [Human motion] [Human motion modeling] [Imitation Learning] [Inference Optimization] [Linux] [Machine Learning] [Model Quantization] [Model Training] [Motion Control] [Motion Modeling] [Multimodal Models] [Python] [PyTorch] [Reinforcement Learning] [Robot motion] [Robot Motion Control] [Robot System Integration] [Simulation-based learning] [System Integration] [Tactile sensing]
Educational requirements:
[Bachelor's Degree]
Role(s):
[AI Algorithm Engineer] [Algorithm Engineer] [Embodied AI Algorithm Engineer] [Engineer] [Research Scientist] [Robotics Research Scientist] [Scientist]