AI Research Engineer (Multi-Modal Reinforcement Learning)
Tasks
- Analyze model behavior across modalities
- Build scalable reinforcement learning infrastructure for distributed training
- Create simulation environments and datasets for training and evaluation
- Design and execute evaluation protocols for reproducibility
- Develop reinforcement learning paradigms using environment feedback
- Develop reward modeling strategies to improve alignment
- Publish research to leading AI conferences
- Research multi modal reinforcement learning methods
Perks/Benefits
- Autonomy
- Fully remote
- Global First Work Environment
- High-impact research
- Innovation culture
- Research publication support
Skills/Tech-stack
Autoregressive models | Deep learning | Diffusion Models | Distributed Training | Experimentation Frameworks | Machine Learning | Multi-Modal | Multi-Modal Learning | Optimization | Policy Optimization | PyTorch | Reinforcement Learning | Reward Modeling | Simulation
Education
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