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.
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 reinventing the future of ecommerce for enthusiasts.
The Foundation Models team is at the forefront of this transformation. We are building next-generation Generative AI and foundation-model capabilities that power intelligent experiences across eBay at global scale. From advanced retrieval systems to multimodal understanding, our work directly shapes how customers discover, evaluate, and engage with inventory across the marketplace.
We are seeking anApplied Researcherto join our Foundation Models team as a hands-on individual contributor. In this role, you will develop, evaluate, and improve AI and foundation-model techniques that support customer-facing and platform experiences at eBay scale. You will work closely with applied researchers, machine learning engineers, product partners, and platform teams to turn research ideas and prototypes into measurable capabilities with customer and business impact.
This is a hands-on applied research role for someone who combines strong machine learning expertise, sound experimental judgment, and the ability to contribute to practical, scalable AI capabilities.
This is an opportunity to:
1. Research and evaluate machine learning and Generative AI capabilities for large-scale ecommerce applications
2. Contribute to applied research in areas such as LLMs, retrieval-augmented generation, embeddings, multimodal modeling, ranking, agentic systems, and feedback-driven learning
3. Improve modeling approaches, training methods, adaptation techniques, and evaluation frameworks for foundation-model-powered ecommerce experiences
4. Design and run experiments to measure model quality, robustness, efficiency, and customer impact
5. Develop learning systems that improve from feedback signals, including reinforcement learning, preference optimization, reward modeling, bandits, and online/offline feedback loops
6. Analyze model behavior, failure modes, and data patterns to identify limitations and propose practical improvements
7. Build training, fine-tuning, evaluation, and experimentation pipelines for machine learning models
8. Collaborate with senior applied researchers, machine learning engineers, and platform teams in advancing promising prototypes toward production
9. Collaborate with engineering, product, and platform teams to integrate AI capabilities into eBay experiences
10. Stay current with advances in machine learning, Generative AI, and foundation models, and evaluate relevant techniques through hands-on experimentation
11. Contribute to scientific and technical standards through structured experimentation, peer review, documentation, and clear technical communication
12. Contribute to publications, patents, internal research reviews, and technical discussions where appropriate
What you will bring:
13. Master’s, PhD, or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field with 4 or more years of relevant work experience
14. Strong hands-on experience developing, evaluating, and improving machine learning models or foundation-model capabilities
15. Solid understanding of machine learning, NLP, Large Language Models, neural architectures, embeddings, retrieval, ranking, personalization, or multimodal modeling
16. Experience with model training, fine-tuning, adaptation, evaluation, benchmarking, and performance analysis
17. Experience with feedback-driven learning systems, such as preference learning, reward modeling, bandits, reinforcement learning, or continuous model improvement loops
18. Ability to design experiments, define meaningful metrics, interpret results, and communicate findings clearly
19. Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar
20. Experience working with large-scale datasets, model training or evaluation pipelines, and applied research workflows
21. Ability to translate product or platform problems into concrete research questions and practical solution approaches
22. Ability to consider tradeoffs across model quality, latency, cost, reliability, and maintainability
23. Strong problem-solving skills and the ability to work effectively in ambiguous technical areas
24. Good collaboration and communication skills, with experience working across research, engineering, product, or platform teams
25. A strong sense of ownership and a track record of delivering meaningful applied research or machine learning contributions
26. Experience contributing to applied research impact, such as publications, patents, shipped model improvements, productionalizing research prototypes, or measurable product outcomes
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. We will make every effort to respond to your request for accommodation as soon as possible. View our to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
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