The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Applied Scientist to support adoption and enable customization of Amazon Nova. The role focuses on developing state-of-the-art services and tools for model customization, including supervised fine-tuning, reinforcement learning, and knowledge distillation across large language models. As an Applied Scientist, you will play a important role in developing advanced customization capabilities that enable enterprises to build highly performant application-specific models without the need for training models from scratch. Your work will directly impact how companies leverage Amazon Nova models for their specific use cases.

- Contribute to the development of novel customization techniques including extended post-training, continued pre-training, and advanced knowledge distillation

- Collaborate with cross-functional teams to design and implement enterprise-ready tooling for various training techniques on Amazon SageMaker

- Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO)

- Develop and enhance preference learning algorithms and training curricula for customer-specific applications

- Create robust evaluation frameworks for assessing model performance across different domains and use cases

- Contribute to the development of the Responsible AI toolkit, including creating training and evaluation datasets for model alignment

- Design and implement secure access mechanisms for early model checkpoints and weights

- Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation