AI Research Engineer (Multi-Modal Reinforcement Learning)
Tasks
- Analyze model behavior across modalities
- Create simulation environments and datasets for training and benchmarking
- Design evaluation protocols for reproducibility
- Design scalable reinforcement learning infrastructure for distributed training
- Develop reinforcement learning paradigms for improved performance
- Develop reward modeling strategies for alignment and stability
- Publish research in AI conferences
- Research reinforcement learning methods for multi modal systems
Perks/Benefits
- Access to research infrastructure
- Fully remote
- Global First Work Environment
- Innovation culture
- Research publication support
Skills/Tech-stack
Autoregressive models | Cross-modal alignment | Diffusion Models | Distributed Training | Evaluation | Machine Learning | Modal Alignment | Multi-Modal | Multi-Modal Learning | Optimization | Policy learning | PyTorch | Reinforcement Learning | Reward Hacking | Reward Modeling | Simulation
Education
Roles
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