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Applied Scientist III - LLMs and NLP, Pricing Intelligence

Job ID: 2656166 | Amazon.com Services LLC - A57

DESCRIPTION

As 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 responsibilities
- Implement 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 team
Within Pricing & Promotions Science, the Product Intelligence team leverages billion-scale multi-modal data on billions of Amazon and external competitor products to build advanced machine learning models for product similarity, substitutability, error detection & correction, and probabilistic price estimation. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.

BASIC QUALIFICATIONS

- 5+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Expertise in deep learning and/or LLM methods
- A track record of balancing project delivery with longer term research, demonstrated via publications, or contributions to the open source community.
- Proficiency in programming languages such as Python and frameworks like TensorFlow, PyTorch
- Proven written and verbal technical communication with the ability to present complex topics clearly to audiences with varying levels of technical familiarity

PREFERRED QUALIFICATIONS

- Experience delivering and scaling AI/ML based solutions involving Probabilistic Forecasting, LLMs, Active Learning, Human Annotation,
- Experience of influencing business or company strategy through cutting edge research and long term science vision
- Experience partnering with academic institutions for collaborations and talent acquisition

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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 https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.