
Buy, sell, and discover.
Applied Researcher - Query Science at eBay
About the role
At e Bay, 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 e Bay 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 e Bay.
What you will accomplish:
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Tackle advanced AI challenges in Query Science and NLP at e Bay.
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Collaborate with researchers and engineers on cutting-edge technologies.
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Contribute to solving complex problems that impact e Bay's platform.
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Help shape the technical vision for query understanding.
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Apply software engineering best practices to improve development experience.
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Build offline data pipelines for ML model training and validation.
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Design and deploy web services for serving real-time inference algorithms.
What you will bring:
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A PhD in Machine Learning/AI or related fields, or at least two years of industry experience the field;
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Proven track record of applied research in AI/ML;
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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;
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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);
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Experience or interest in working with all kinds of Artificial Neural Networks and Large Language Models;
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Experience or interest in working with service-oriented architectures and frameworks (e.g. Spring Boot);
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Experience or interest in working with cloud computing solutions (Docker, Kubernetes, etc.);
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Proven ability to work independently and make good decisions with minimal direction;
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Strong communication skills (fluent English, both verbal and written)
Additional Details
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, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. 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 for people with disabilities.
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Required skills
Machine learning
NLP
Information retrieval
Query understanding
Deep learning
Experimentation
Python
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About eBay

eBay
PubliceBay Inc. is an American multinational e-commerce company based in San Jose, California, that allows users to buy or view items via retail sales through online marketplaces and websites in 190 markets worldwide.
10,001+
Employees
San Jose
Headquarters
$28.1B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.2
Compensation
2.8
Culture
4.1
Career
3.0
Management
2.7
72%
Recommend to a friend
Pros
Supportive team culture and colleagues
Good benefits and health coverage
Flexible work arrangements
Cons
Management issues and lack of direction
Limited career advancement opportunities
Compensation below expectations
Salary Ranges
2,735 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Science Analyst 2
1 reports
$174,200
total per year
Base
$134,000
Stock
-
Bonus
-
$174,200
$174,200
Interview experience
4 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 75%
Negative 25%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
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