Senior Applied Scientist
Tasks
- Build and maintain pipelines to evaluate generative models quality efficiency and safety
- Collaborate to transfer model alignment improvements into products
- Conduct post-training research and development for generative AI models
- Design and evaluate RLHF techniques for instruction following and safety
- Develop and evaluate direct preference optimization methods
- Develop distillation compression and inference acceleration methods
- Implement research ideas in Python for production
- Mentor peers and junior researchers
- Perform supervised fine tuning for model alignment
- Train and use reward modeling for preference optimization
Perks/Benefits
- N/A
Skills/Tech-stack
Diffusion Models | Direct Preference Optimization | Fine Tuning | Human Feedback | Inference acceleration | Large Scale Training | Large-scale | Learning from Human Feedback | ML Infrastructure | Machine Learning | Model Compression | Model Distillation | Preference optimization | PyTorch | Python | Reinforcement Learning | Reinforcement Learning from Human Feedback | Reward Modeling | Supervised Fine Tuning | Transformers
Education
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