Machine Learning: Multimodal Foundation Models
Tasks
- Build multimodal policies
- Deploy models for edge inference and optimize performance
- Design training loop end to end
- Develop unified multimodal representations
- Diagnose failure modes
- Implement grounding with kinematic constraints
- Improve cross modal reasoning
- Improve data mixtures and evaluation
- Integrate models into robotic stacks
- Train debug and iterate large scale experiments
Perks/Benefits
Skills/Tech-stack
C++ | Data Engineering | Deep learning | Distributed Training | Edge inference | GPU Computing | Human Feedback | Language Models | Large Language Models | Learning from Human Feedback | Machine Learning | Model Evaluation | Multimodal Learning | Pretraining | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Rust
Education
N/A
Regions
Countries
States
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