Job Description

DESCRIPTION

Are 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 QUALIFICATIONS

10+ 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.

Job Tags

Full time, Worldwide,

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