Amazon
Applied Scientist, Catalog AI, Amazon Selection and Catalog Systems
Amazon, San Francisco, California, United States, 94199
Applied Scientist, Catalog AI, Amazon Selection and Catalog Systems
Job ID: 3153966 | Amazon.com Services LLC
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).
We are seeking a passionate, talented, and inventive individual to join the Catalog AI team and help build industry-leading technologies that customers will love. You will apply machine learning and large language model techniques, such as fine-tuning, reinforcement learning, and prompt optimization, to solve real customer problems. You will work closely with scientists and engineers to experiment with new methods, run large-scale evaluations, and bring research ideas into production.
Key job responsibilities
Design and implement LLM-based solutions to improve catalog data quality and completeness
Conduct experiments and A/B tests to validate model improvements and measure business impact
Optimize large language models for quality and cost on catalog-specific tasks
Collaborate with engineering teams to deploy models at scale serving billions of products
Basic Qualifications
PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience with popular deep learning frameworks such as MxNet and TensorFlow
Preferred Qualifications
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience with Large Language Model (LLM) and Foundational Model fine-tuning, or reinforcement learning techniques
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected
#J-18808-Ljbffr
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).
We are seeking a passionate, talented, and inventive individual to join the Catalog AI team and help build industry-leading technologies that customers will love. You will apply machine learning and large language model techniques, such as fine-tuning, reinforcement learning, and prompt optimization, to solve real customer problems. You will work closely with scientists and engineers to experiment with new methods, run large-scale evaluations, and bring research ideas into production.
Key job responsibilities
Design and implement LLM-based solutions to improve catalog data quality and completeness
Conduct experiments and A/B tests to validate model improvements and measure business impact
Optimize large language models for quality and cost on catalog-specific tasks
Collaborate with engineering teams to deploy models at scale serving billions of products
Basic Qualifications
PhD, or Master’s degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience with popular deep learning frameworks such as MxNet and TensorFlow
Preferred Qualifications
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience with Large Language Model (LLM) and Foundational Model fine-tuning, or reinforcement learning techniques
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected
#J-18808-Ljbffr