Amazon Principal Applied Scientist Amazon 

United States, California, Palo Alto 

716590334

Key job responsibilities
As a Principal Applied Scientist in Search, you will possess deep expertise in machine learning and data science, with specializations in information retrieval, recommendations, ranking, large language models, and generative AI across various modalities. The role involves solution alignment across multiple partners, such as front-end, relevance, ranking, and personalization teams. You will collaborate with teams of scientists and engineers to translate business and functional requirements into concrete deliverables, leading strategic efforts to enhance upper funnel search customer experiences. You will design integrated solutions efficiently delivered across all contributing stakeholder teams, driving alignment among these tech teams in the short term and influencing their future roadmaps in the long term to support our experimentation roadmap. Responsible for overall solution quality, this role will focus on improving experimentation velocity and, in the future, facilitating partner development on upper funnel customer experiences. This role ensures we are building scalable solutions with smart checks on data quality centrally, navigating the ambiguity inherent in this new area. You will make critical judgements to select the best technical solutions for both short and long-term experimentation objectives, bringing clarity from ambiguity, structuring tradeoff decisions, and effectively communicating on technically contentious topics. Finally, you will engage with academic partners to augment our in-house talent with access to the latest research and expert mentoring.
Palo Alto, CA, USA

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

1. Over 10 years of post-PhD research experience in machine learning.
2. Strong mathematical and statistical skills.
3. Demonstrated success in algorithm design and product development.
4. Publications in top-tier conferences or journals.
5. Experienced in mentoring and managing senior technical staff.
6. Proven business acumen, balancing multiple aspects of projects including technology and product strategies.
7. Effective communicator with diverse audiences.
8. Experience with large data sets and building scalable models.