Sr. Manager of Applied Science - Catalog Services, Product GenAI

Position: Sr. Manager of Applied Science - Catalog Services, Product Knowledge GenAI
Description

The Catalog Services Product Knowledge team is seeking a Sr. Applied Science Manager for leading initiatives for understanding, and scaling organization of product schema information. Our vision is simple: build AI systems that are capable of a deep product understanding, so we can organize and scale the catalog metadata (schema) for Amazon e-commerce catalog worldwide. This is a complex problem because the magnitude of products entities (attributes, values, constraints) to be modeled to cover all the Amazon products worldwide.

You will lead a team of experienced Applied Scientists (direct reports) to create models and deliver them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML and GenAI techniques that will scale our catalog artifacts with a high precision across countries and languages.

The leader will drive investments in machine learning, natural language processing, GenAI, to solve real world problems  team's output affects the velocity at which we build product schema and support the largest e-commerce catalog and impact million of customers. The team builds solutions ranging from automatic generation of product metadata, classification of entities, validation of concepts against customer traffic, creation of agents solving complex  tasks mimicking human decisions at high precision, etc;

all these developments drive true understanding of products at scale.

We are looking for an entrepreneurial, experienced Sr. Applied Science Manager who can turn a group of Machine Learning Scientists (PhD's in NLP, ML, GenAI) to produce best in class solutions. The ideal candidate has deep expertise in one or several of the following fields:
Generative AI, Agents, LLMs, Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Natural Language Processing. S/he has a strong publication record at relevant academic venues and proven experience in launching products/features in the industry.

Key job responsibilities

In this team, you will:

- Manage business and technical  requirements, design, be responsible for the overall coordination,  quality, productivity and will be the primary point of contact for  world-wide stakeholders of programs and goals that you lead.

- Partner  with scientists, economists, and engineers to help deliver scalable ML  scaled models, while building mechanisms to help our customers gain and  apply insights, and build road maps for the projects you own.

- Track  service levels and schedule adherence, and ensure the individual  stakeholder teams meet and exceed their performance targets.

- Be expected to discover, define, and apply scientific, engineering, and business best practices.

- Manage and develop Applied Scientists (direct reports with a respective team).

About the team

The team's mission is to infer knowledge, understand, and derive product schema for all Amazon products entering the Catalog. The work is critical to power drive policies on how products will be merchandised, guide Selling Partners, inform models how to infer attributes. All this information drives the navigational Taxonomy, Search and Detail Page experiences, impacting million of customers. This is an already formed team with experience leading programs spanning services and ML initiatives.

The leader collaborates closely with Software Managers, Sr. Leaders, and has exposure to multiple peer teams at Amazon who rely on this team's developments.

Basic Qualifications

- 10+ years of building large-scale machine learning and AI solutions at Internet scale experience

- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)

- Experience managing and quantifying improvements in customer experience or value for the business resulting from research outcomes

- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track

Preferred Qualifications

- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)

- 10+ years of practical work applying ML to solve complex problems for…