具身智能算法实习生 (Manipulation)
Tasks
- Collect data and debug results
- Deploy and quantize models for embedded devices
- Develop multimodal large model algorithms
- Evaluate model performance
- Implement perception to action pipelines
- Optimize pretraining data
- Perform supervised fine-tuning
- Reproduce and improve state of the art algorithms
- Run reinforcement learning and preference optimization
- Validate algorithms in simulation and real robots
Perks/Benefits
- N/A
Skills/Tech-stack
CLIP | Code debugging | Data Preprocessing | Deep learning | Diffusion Models | Embedded Systems | Fine Tuning | Isaac-Gym | LLaVA | Language Models | Large Language Models | Model Quantization | Multimodal Models | Performance Evaluation | PyTorch | Python | ROS | ROS2 | Reinforcement Learning | SAPIEN | Simulation | Supervised Fine Tuning | Transformer | Vision Transformer
Education
Roles
AI | AI Research Intern | Engineer | Intern | Learning Engineer | Machine Learning Engineer | Research Intern
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