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
- Design evaluation protocols for reproducibility
- Develop reward modeling strategies
- Explore reinforcement learning paradigms for improved performance
- Publish research in AI conferences
- Research reinforcement learning methods for multi modal systems
Perks/Benefits
Skills/Tech-stack
Autoregressive models | Dataset curation | Deep learning | Diffusion Models | Distributed Training | Exploration Exploitation Tradeoff | Exploration/exploitation | Machine Learning | Multi-Modal | Multi-modal AI | Optimization | Policy learning | PyTorch | Reinforcement Learning | Reward Modeling | Sample efficiency | Simulation Environments | Training stability
Education
Roles
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