Applied Researcher 2

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

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 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.

What you will accomplish:

• 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.

What you will bring:

• 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.

Additional Details

The base pay range for this position is expected in the range below:

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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