Amazon Senior Applied Scientist AGI Customization Services 

United States, Washington, Bellevue 

185271666

As a Senior Applied Scientist, you will play a critical 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 enterprises leverage Amazon Nova models for their specific use cases.
Key job responsibilities
- Lead the development of novel customization techniques including extended post-training, continued pre-training, and advanced knowledge distillation- Design and execute experiments to optimize model accuracy, latency, and cost across different customization approaches (SFT, DPO, PPO)- 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
- Think big about the evolution of model customization technologies over a multi-year horizon, identifying new opportunities to enhance enterprise AI capabilities
- Communicate technical insights and results to both technical and non-technical stakeholders through presentations and documentation
- Monitor and analyze trends in AI to continuously refine the customization strategy, ensuring alignment with industry best practices and emerging standards

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 5+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

- PhD in Computer Science, Machine Learning, or a related field, with a focus on Gen AI and reinforcement learning
- Experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning
- Programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch
- Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
- Experience with patents or publications at top-tier peer-reviewed conferences or journals