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 Agentic Systems Research team is building the next generation of intelligent systems that assist buyers and sellers across eBay’s global marketplace. Our mission is to develop AI agents capable of reasoning, planning, and acting across complex commerce environments, helping users discover products, make decisions, manage inventory, and complete transactions more effectively.
As an Applied Researcher, you will work at the intersection of large language models, retrieval systems, recommender systems, and agent architectures to develop AI systems that can operate reliably in real-world commerce workflows. You will collaborate with engineers, product leaders, and other researchers to transform research ideas into production systems used by millions of customers.
This role combines applied research, experimentation, and system development to advance the science and practice of agentic AI in large-scale marketplaces.
What you will accomplish:
Design and prototype agentic AI systems capable of multi-step reasoning, planning, and tool use across eBay’s marketplace infrastructure.
Develop and evaluate LLM-based systems for commerce tasks such as product discovery, listing creation, pricing guidance, customer support, and seller assistance.
Advance retrieval-augmented generation (RAG) and knowledge-grounded AI techniques for reasoning over structured marketplace data including catalog information, listings, and seller tools.
Build robust evaluation frameworks for agentic systems, including offline evaluation, synthetic task generation, human evaluation, and online experimentation.
Collaborate closely with engineering teams to translate research prototypes into reliable production systems operating at large scale.
Analyze large-scale datasets to understand user behavior and improve AI-driven relevance, personalization, and decision support.
Contribute to the broader AI research community through technical publications, patents, and conference presentations where appropriate.
What you will bring:
Education: Ph.D. or M.S. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical field.
Technical Expertise:
Strong understanding of modern machine learning and deep learning techniques, particularly in areas such as: Large Language Models (LLMs), Natural Language Processing, Recommender systems and personalization, Information retrieval and search, Retrieval-augmented generation (RAG) etc.
Experience working with large-scale datasets and distributed data processing systems.
Strong programming skills in Python and modern ML frameworks, with experience working with large-scale data platforms such as Spark or similar distributed systems.
Research & Problem Solving
Experience designing and running machine learning experiments, including hypothesis development, ablation studies, error analysis, and model iteration.
Familiarity with evaluation methodologies such as offline metrics, human evaluation, and A/B testing.
Strong analytical skills and ability to derive insights from large-scale behavioral data.
Collaboration & Communication
Excellent written and verbal communication skills with the ability to explain complex technical concepts clearly.
Ability to work effectively in cross-functional teams spanning research, engineering, and product.
Bonus Experience
Experience with agentic AI systems, such as:
Tool-using LLMs
Multi-step workflows and planning
Memory or stateful agents
Orchestration frameworks
Agent evaluation and reliability techniques
Experience applying machine learning to large-scale consumer products or e-commerce systems.
Additional Details
The base pay range for this position is expected in the range below:
C$142,400 - C$190,100Base 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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