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.
About the team
The vision of the Search and Conversational Shopping AI Team is to revolutionize the search and shopping experience through technological innovations in advanced AI and machine learning. We focus on enhancing query understanding, navigational and upper funnel search, developing LLM-based AI assistants, and more. Our goal is to create intuitive, personalized search interfaces that seamlessly connect customers with products, enhancing satisfaction, engagement, and transforming e-commerce interactions.
BASIC QUALIFICATIONS
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.
PREFERRED QUALIFICATIONS
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.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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.