AI Research Engineer (Multi-Modal Reinforcement Learning)
Tasks
- Analyze model behavior across modalities
- Conduct reinforcement learning research for multimodal systems
- Create simulation environments and datasets for training and benchmarking
- Design and execute evaluation protocols for reproducible experiments
- Design scalable RL infrastructure for distributed training and evaluation
- Develop next generation RL paradigms
- Develop reward modeling strategies for alignment and training stability
- Publish research in leading AI conferences
Perks/Benefits
Skills/Tech-stack
Autoregressive models | Diffusion Models | Distributed Training | Experimentation Frameworks | Exploration | Machine Learning | Multi-Modal | Multi-Modal Learning | Optimization | Policy learning | PyTorch | Reinforcement Learning | Reward Modeling | Sample efficiency | Simulation Environments | Training stability
Education
Roles
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