AI Research Engineer (Multi-Modal Reinforcement Learning) - 100% Remote Worldwide
Tasks
- Analyze policy performance bottlenecks across modalities
- Benchmark reinforcement learning performance across multimodal tasks
- Curate multimodal simulation environments and datasets
- Design reinforcement learning infrastructure for distributed training
- Develop reinforcement learning paradigms from environment feedback
- Develop reward modeling to improve training stability
- Publish research findings in top-tier conferences
- Research reinforcement learning algorithms for multimodal models
Perks/Benefits
Skills/Tech-stack
Audio Processing | Autoregression | Autoregressive models | Computer Vision | Deep learning | Diffusion Models | Distributed Training | Exploration/exploitation | Generative Models | Language Processing | Multi-Modal | Multi-Modal Learning | Natural Language | Natural Language Processing | Policy Optimization | PyTorch | Reinforcement Learning | Reward Hacking | Reward Modeling | Sample efficiency | Training stability
Education
Roles
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