Senior Applied Scientist, AGI Customization Services

The Artificial General Intelligence (AGI) Customization Team is seeking a highly skilled and experienced Senior 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 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
- 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
- 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.