Amazon Senior Principal Applied Scientist Amazon Rufus 

United States, California, Palo Alto 

230104421

Key job responsibilities
As a Senior Principal Applied Scientist in Search and Shopping, you will have deep expertise in machine learning and data science, with specialties in large language models, reinforcement learning, supervised learning, and generative AI across various modalities. This role involves aligning solutions with multiple partners including product teams, experience design and foundational model teams. You will lead teams of scientists and engineers in translating business and functional requirements into concrete deliverables, driving strategic initiatives to enhance AI-driven customer experiences.Your responsibilities include designing integrated solutions that are efficiently implemented across all stakeholder teams, maintaining alignment in the short term while influencing long-term strategic roadmaps to support ongoing experimentation. You will ensure high solution quality, focusing on accurately understanding and responding to customers through AI assistants, enhancing the speed of experiments and iterations of customer experience.Additionally, this role involves building scalable solutions with robust checks on human feedback, managing the complexities of customer intents, and reinforcing learning algorithms with human feedback. You will make critical decisions on the best technical solutions for both immediate and future needs, clarify complex issues, manage trade-offs, and communicate effectively about technical challenges.Finally, you will work with academic partners to enhance our team's capabilities by accessing the latest research and expert mentoring, ensuring our approaches remain cutting-edge.Palo Alto, CA, USA

1. Graduate degree in Computer Science, Math, or a related field.
2. Experience in developing large language models and reinforcement learning solutions for generative AI applications.
3. Experience in developing AI, ML, and NLP systems, with a proven ability to deliver projects successfully.
4. Skilled in managing large, cross-functional projects with evolving requirements from start to finish.
5. Strong foundations in data structures, algorithm design, and complexity analysis.
6. Ability to strategize for ML platforms focusing on recommender systems, ranking, and customer interaction features.
7. Exceptional ability to understand customer needs, propose alternative technical and business solutions, and deliver on tight deadlines.
8. Record of peer-reviewed scientific publications in applied science.

1. Over 15 years of post-PhD research experience in machine learning.
2. Strong mathematical and statistical skills.
3. Profound knowledge of foundational models, including large language models across multiple modalities, reinforcement learning, supervised learning, and other cutting-edge techniques in generative AI.
4. Demonstrated success in algorithm design and product development.
5. Publications in top-tier conferences or journals.
6. Experienced in mentoring and managing senior technical staff.
7. Proven business acumen, balancing multiple aspects of projects including technology and product strategies.
8. Effective communicator with diverse audiences.
9. Experience with large data sets and building scalable models.