Applied Researcher I (AI Foundations, LLM Customization, Finetuning, Reinforcement Learning)
Tasks
- Build AI foundation models from design through implementation
- Conduct applied research on emerging AI methods
- Develop fine tuning and reinforcement learning workflows
- Evaluate validate and deploy AI models at scale
- Leverage PyTorch AWS and Huggingface to analyze large data
- Partner cross functional teams to deliver AI powered products
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Data labeling | Dataset curation | Deep learning | Distributed Training | Fine Tuning | Huggingface | Human Feedback | Instruction Tuning | Language Models | Language Processing | Large Language Models | Learning from Human Feedback | Lightning | Machine Learning | Model Explainability | Model Robustness | Natural Language | Natural Language Processing | PyTorch | Reinforcement Learning | Reinforcement Learning from Human Feedback | Self-Supervised Learning | Self-supervised | Supervised Fine Tuning | Supervised Learning | Tokenization | Training Optimization | Transfer Learning | Vector Databases
Education
Roles
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