Amazon
Sr. Applied Scientist - LLMs and NLP, Retail Pricing Science
Amazon, Santa Clara, California, us, 95053
Sr. Applied Scientist - LLMs and NLP, Retail Pricing Science
Job ID: 2816029 | Amazon.com Services LLCAs a Senior Applied Scientist specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) in the Product Intelligence team, you will lead the development of machine learning solutions. Your work will leverage the latest LLMs and multimodal models to enhance product graphs, measure entity similarity, perform entity linking, and attribute normalization, and apply advanced reasoning methods for a deeper understanding of products. You will also lead research projects to tackle unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication.
This high-impact role is critical to our core business, influencing the reliability of information for billions of products on Amazon's platform, and impacting the shopping journey for hundreds of millions of customers. The systems you build will be used to monitor Amazon's entire product selection to ensure their quality, the availability of accurate price distributions, and more.
We seek an experienced scientist with deep knowledge of LLMs and NLP, and a good understanding of traditional machine learning and quantitative methods. The role will also require cross-functional collaboration skills, and staying up to date with the latest advancements in Generative AI.
Key job responsibilitiesImplement and deploy systems that leverage LLMs and other techniques to address some of hardest problems in the pricing space.Set scientific standards and see the big picture to influence Amazon's long-term vision for retail pricing science.Work cross-functionally with various teams to align machine learning initiatives with business goals and execute them successfully.Lead research projects and participate in the publication of external academic papers at top conferences and journals.About the teamRetail pricing science is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.BASIC QUALIFICATIONS
PhD, or Master's degree and 10+ years of applied research experience4+ years of applied research experience4+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative fieldExperienced with ML techniques in anomaly and error detection. Strong hands-on background with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with weak supervision and semi-supervised techniques.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.
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Job ID: 2816029 | Amazon.com Services LLCAs a Senior Applied Scientist specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) in the Product Intelligence team, you will lead the development of machine learning solutions. Your work will leverage the latest LLMs and multimodal models to enhance product graphs, measure entity similarity, perform entity linking, and attribute normalization, and apply advanced reasoning methods for a deeper understanding of products. You will also lead research projects to tackle unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication.
This high-impact role is critical to our core business, influencing the reliability of information for billions of products on Amazon's platform, and impacting the shopping journey for hundreds of millions of customers. The systems you build will be used to monitor Amazon's entire product selection to ensure their quality, the availability of accurate price distributions, and more.
We seek an experienced scientist with deep knowledge of LLMs and NLP, and a good understanding of traditional machine learning and quantitative methods. The role will also require cross-functional collaboration skills, and staying up to date with the latest advancements in Generative AI.
Key job responsibilitiesImplement and deploy systems that leverage LLMs and other techniques to address some of hardest problems in the pricing space.Set scientific standards and see the big picture to influence Amazon's long-term vision for retail pricing science.Work cross-functionally with various teams to align machine learning initiatives with business goals and execute them successfully.Lead research projects and participate in the publication of external academic papers at top conferences and journals.About the teamRetail pricing science is a centralized diverse team of STEM scientists that develop statistical, ML, RL, optimization and economic models that drive pricing for products sold by Amazon worldwide, as well as monitoring of prices and experimentations in pricing. The team has a dual focus on competitiveness and long term financial optimality.BASIC QUALIFICATIONS
PhD, or Master's degree and 10+ years of applied research experience4+ years of applied research experience4+ years of building machine learning models for business application experienceExperience programming in Java, C++, Python or related languageExperience with neural deep learning methods and machine learningPREFERRED QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative fieldExperienced with ML techniques in anomaly and error detection. Strong hands-on background with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with weak supervision and semi-supervised techniques.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.
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