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Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.
Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.
About the team and the role:
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.
What you will accomplish:
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, evaluated, and maintained across teams.
Share your work and learnings through internal tech talks, publications, and participation in forums and conferences, helping to strengthen eBay’s reputation in applied research for e-commerce search.
What you will bring:
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.
Additional Details
The base pay range for this position is expected in the range below:
C$118,000 - C$157,500
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including RRSP eligibility, various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
This job posting relates to an existing vacancy within eBay.
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at [email protected]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility.
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