Principal Applied Scientist - LLMs, Price Understanding, Estimation, and ValidationJob ID: 2851503 | Amazon.com Services LLC
Amazon's Pricing & Promotions Science is seeking a driven Principal Applied Scientist to harness planet scale multi-modal datasets and navigate a continuously evolving competitor landscape, in order to build and scale an advanced self-learning scientific price estimation and product understanding system, regularly generating fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide.
We are looking for a talented, organized, and customer-focused technical leader to join our Product Intelligence science group, with a charter to derive deep neural product relationships, quantify substitution and complementarity effects, and publish trust-preserving probabilistic price ranges on all products listed on Amazon.
This role requires an individual with excellent scientific modeling and system design skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced leader who is a self-starter comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.
Key Job ResponsibilitiesDevelop the team. Mentor a highly talented group of applied machine learning scientists & researchers.See the big picture. Shape long term vision for Amazon's science-based competitive, perception-preserving pricing techniques.Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale.Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems.Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery.Deliver Impact. Develop, Deploy, and Scale Amazon's next generation foundational price estimation and understanding system.About the TeamWithin Pricing & Promotions Science, the Product Intelligence team leverages planet 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 QUALIFICATIONSPh.D. or Master's degree in Computer Science, Statistics, Machine Learning, Natural Language Processing, Financial Modeling, or related field.10+ years of broad AI/ML research experience on large-scale industry problems in pricing, time series, forecasting, trading, recommendation, or natural language domains.5+ years of experience technical leadership of applied science teams.5+ years of experience with AWS or Amazon ML tech stack and tooling.Expertise in deep learning 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 QUALIFICATIONSExperience 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. Posted: September 4, 2024 (Updated 1 day ago)
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