Applied Researcher 2

eBay•Toronto, ON

About The Position

eBay is a global commerce leader that connects millions of buyers and sellers around the world and creates economic opportunity for individuals, entrepreneurs, businesses and organizations of all sizes. The Search Query Understanding team is the largest contributor to eBay’s search and query processing stack and drives a significant portion of the company’s revenue. This team builds core e-commerce search capabilities such as query rewriting, query annotation and classification, query recovery, and related systems using state-of-the-art machine learning tailored to large-scale user behavioral signals. As an Applied Researcher on this team, you will help define and build the next generation of query understanding products that power how people discover items on eBay. You will work on complex problems like understanding query intent, entity resolution and tagging, categorization, intelligent query rewrites and clustering, and the application of knowledge graphs to search. You will join a results-oriented, collaborative, and fun environment where people who think differently, deliver impact, and win together are supported to grow their careers.

Requirements

MS or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
1–3 years of relevant industry experience with a PhD, or 3–5 years with an MS, applying machine learning to real-world problems such as classification, regression, NLP, gradient-boosted models, recommendation, clustering, fraud detection, or deep learning.
Hands-on experience with large-scale data processing technologies (for example Hadoop, SQL, or Spark) and building end-to-end data and model pipelines.
Proficiency in at least one statistical or scripting language such as Python or R, and experience with at least one of Java, Scala, or C/C++ for building robust, production-grade solutions.
A track record of scientific contribution demonstrated by two or more related publications in quality conferences or journals, and the ability to communicate complex ideas clearly to both technical and non-technical audiences.
Commitment to inclusive, collaborative ways of working, with the ability to partner effectively across diverse teams, contribute to a positive team culture, and help make eBay a place where everyone feels they belong.

Responsibilities

Develop and deploy scientifically rigorous machine learning models and data pipelines that directly improve search relevance, query understanding, and downstream business metrics for millions of buyers and sellers.
Translate large-scale behavioral and content data into practical, high-impact solutions for problems such as query intent understanding, entity resolution, classification, and intelligent query rewriting.
Partner with engineers, product managers, and other scientists to design experiments, validate hypotheses, and promote standard scientific methodologies that raise the bar for search quality across eBay.
Lead and contribute to innovative research that advances the state of the art in areas like NLP, recommendation, and deep learning, and translate research outcomes into production-ready systems.
Share your work with internal and external communities by presenting novel results, prototypes, and best practices in technical forums, workshops, and relevant conferences.
Continuously learn and grow by exploring emerging techniques, tools, and architectures in machine learning and big data, and by mentoring and collaborating with colleagues across disciplines.