Amazon Senior GenAI Data Scientist Amazon Bedrock 

United States, New York, New York 

979765008

As part of the Generative AI Worldwide Specialist organization, you will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures. You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review.Key job responsibilities
- Thought Leadership and External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS re:Invent.

- 5+ years of Data Scientist or Machine Learning Solutions Architect experience preferably with a focus on AI/ML ethics and security .
- 5+ years of experience with Python to analyze datasets, train , evaluate, deploy, and optimize models.
- - 3 years Expertise in Responsible AI practices, such as bias mitigation, fairness evaluation, and ethical AI principles.
- - 3 years experience with AI security best practices, including vulnerability assessments, red teaming, and data access controls.
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 1+ year experience working with technologies related to large language models including LLM architectures, Responsible generative AI, model evaluation, and model customization techniques.
- Proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches.
- Proficient with prompt engineering, embedding model fine tuning and retrieval method evaluation and optimization approaches.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.