Tasks:
- * Adapt models to benchmark data and task interfaces
- * Analyze failure cases and capability limits
- * Compare model performance across tasks and generalization settings
- * Document experiment results and model architectures
- * Reproduce open-source embodied AI models
- * Run inference and evaluation experiments
- * Train and fine-tune models
Perks/Benefits:
Skills/Tech stack required:
[ACT] [Action Representation] [Behavior Cloning] [Conda] [Data Preprocessing] [Diffusion Policy] [Docker] [Fine Tuning] [Git] [GPU Training] [Imitation Learning] [Isaac Sim] [Linux] [Model Evaluation] [Model Fine-tuning] [Model Inference] [Mujoco] [Multimodal Learning] [Python] [PyTorch] [Real-robot deployment] [Reinforcement Learning] [RLBench] [Robosuite] [Robot deployment] [Robot Manipulation] [TensorBoard] [Transformer policies] [VLA models] [W&B]
Educational requirements:
[Bachelor's Degree] [Master's Degree]
Role(s):
[AI Research Intern] [Embodied AI Research Intern] [Intern] [Learning Intern] [Machine Learning Intern] [Research Intern] [Robotics Machine Learning Intern] [Robotics Research Intern]