Sr. Manager, Applied Science, Catalog AI, Amazon Selection and Catalog Systems

Amazon

  • Seattle, WA
  • Permanent
  • Full-time
  • 1 month ago
DESCRIPTIONAre you fascinated by the power of Large Language Models (LLM) and applying Generative AI to solve complex challenges within one of Amazon's most significant businesses? Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world's largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon's customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions.We develop LLM applications that make Catalog the best-in-class source of product information for all products worldwide. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries) and multitude of input sources (millions of sellers contributing product data with different quality).You will lead the Amazon Catalog Science team and own devising the strategy and execution plans that power initiatives ranging from: developing tuning artifacts on top of foundational LLMs, training ML models, performing fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for distilling product information, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale.The right candidate will be a leader who lives and breathes innovation. They'll foster a culture where creative thinking is celebrated and bold ideas can take root. Most importantly, they'll be able to transform this innovative spirit into tangible results, skillfully guiding the team from inspiring vision to real-world impact through careful execution of our strategic roadmap.BASIC QUALIFICATIONS10+ years of building AI models for business application.
  • 5+ years as a science leader or staff/principal level scientist.
  • PhD, or Master's degree and 10+ years of CS, CE, ML or related field experience.
PREFERRED QUALIFICATIONSAdvanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
  • Published research work in academic conferences or industry circles.
  • Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
  • Effective verbal and written communication skills with non-technical and technical audiences.
  • Experience working with large real-world data sets and building scalable models from big data.
  • Thinks strategically, but stays on top of tactical execution.
  • Exhibits excellent business judgment; balances business, product, and technology very well.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $196,900/year in our lowest geographic market up to $340,300/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 . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Amazon