Applied Researcher 1

eBay•Toronto, ON

About The Position

eBay Inc. 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 Query Science team sits at the core of eBay’s Search product and is a key driver of search/query processing and revenue for the company. We are a team of passionate professionals focused on making searching and buying on eBay as efficient and enjoyable as possible. By deeply understanding buyer intent and behavior, we tailor our services to deliver an exceptional shopping experience and set new standards in e-commerce search. Our culture values creativity, experimentation, hard work, and a friendly, fun, and collaborative environment where people can bring their unique perspectives to work every day. We are looking for an Applied Researcher to help build the next generation of query science products for eBay Search. In this role, you will tackle high-scale, technically complex query processing challenges (such as query intent understanding, entity resolution and tagging, categorization, query rewriting, and knowledge graph applications) and play a critical part in redefining query understanding at eBay while partnering closely with cross-functional teams across Search, Engineering, Product, and Analytics.

Requirements

PhD in Computer Science, Artificial Intelligence, Information Retrieval, or a related field (including recent graduates), or a Master’s degree with 1–3 years of relevant industry experience focused on NLP or machine learning.
Hands-on experience applying one or more of the following to real-world, large-scale problems: classification, regression, NLP, clustering, deep learning/neural networks, reinforcement learning, or related machine learning techniques.
Strong background in machine learning, NLP, and search-related technologies, with a demonstrated ability to translate research ideas into effective, production-ready solutions.
Proficiency in Python and at least one of Java, Scala, or C/C++, along with experience using modern ML frameworks and tools; familiarity with big data processing technologies (such as Hadoop, SQL, or Spark) is preferred.
Excellent analytical and problem-solving skills, with a creative and experimental mindset for tackling complex, ambiguous challenges in query understanding.
Strong written and verbal communication skills in English, with the ability to explain technical concepts clearly to diverse audiences and to collaborate effectively across teams, locations, and time zones.

Responsibilities

Design, develop, and deploy end-to-end machine learning and NLP solutions that measurably improve query understanding, retrieval quality, and buyer experience on eBay.
Apply state-of-the-art techniques in NLP, Embedding Based Retrieval (EBR), semantic search, and LLMs to address core e-commerce search problems such as query rewriting, query annotation/classification, and query recovery.
Leverage large-scale user behavioral signals and eBay’s technical ecosystem to build practical, scalable models that drive improvements in search relevance and key business metrics.
Collaborate with partners across Search, Engineering, Product, and Analytics to define high-impact problems, validate scientific approaches through experimentation, and deliver robust features into production.
Champion standard scientific methodologies and best practices for experimentation, evaluation, and model governance, influencing how query understanding solutions are developed and measured across teams.
Share your work and learnings through internal tech talks, external publications, and participation in forums and conferences, helping to strengthen eBay’s reputation in applied research for e-commerce search.