About this role
Applied Researcher - Query Science
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:
The Search Query Science team at eBay is a key driver of the company's search revenue and is growing rapidly. We're building a world-class team that values bold, innovative thinking and rewards impact. Our work focuses on solving core e-commerce search challenges—like query rewriting, annotation, classification, and recovery—using cutting-edge ML algorithms that interpret large-scale user behavior. With a fun, collaborative environment, we're now looking for stellar applied researchers to develop advanced query understanding products. If you're excited by large-scale query processing—intent detection, entity resolution, categorization, expansion and filter recommendation—join us and help redefine query understanding at eBay.
What you will accomplish:
- Tackle advanced AI challenges in Query Science and NLP at eBay.
- Collaborate with researchers and engineers on cutting-edge technologies. Contribute to solving complex problems that impact eBay's platform.
- Help shape the technical vision for query understanding.
- Apply software engineering best practices to improve development experience.
- Build offline data pipelines for ML model training and validation. Design and deploy web services for serving real-time inference algorithms.
What you will bring:
- A PhD in Machine Learning/AI or related fields, or at least two years of industry experience in the field with Proven track record of applied research in AI/ML;
- Knowledge of Machine Learning and Statistics fundamentals: classification, regression, and clustering, dimensionality reduction and feature selection, convex/non-convex optimization, ranking and recommendation, hypothesis testing;
- Strong education in computer science (data structures and algorithms, computational complexity analysis) and proficiency with one or more programming language (Python, Java, C/C++, bash and other scripting languages);
- Experience working with all kinds of Artificial Neural Networks and Large Language Models; service-oriented architectures and frameworks (e.g. SpringBoot); cloud computing solutions (Docker, Kubernetes, etc.);
- Proven ability to work independently and make good decisions with minimal direction;