ML/Applied Research Manager

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.

As part of this focused C2C strategy, eBay continues to invest in the future of circular commerce and the next generation of conscious consumers. With the recent acquisition of Depop, a leading consumer-to-consumer fashion marketplace with a highly engaged Gen Z and Millennial customer base, eBay is rapidly growing its portfolio of complementary C2C businesses while preserving the distinct brand, community, and product experience that make Depop outstanding.

The Depop team is investing in advanced Machine Learning, NLP, LLM/GenAI, RAG, and AI technologies to develop more intelligent and engaging marketplace experiences for our global community.

We are looking for an AI leader and innovator who can lead a team of applied researchers and engineers, hire top talent when necessary, as well as get systems into production at eBay scale. The candidate will work closely with leaders and other teams from our globally distributed organization, including product managers, design, and analytics leaders to brainstorm and enable future personalized recommendation user experiences.

This is an opportunity to:

• Lead and manage a group of applied researchers and engineers who have deep expertise in natural language processing. They also specialize in large language models, AI, recommender systems, and ML production engineering.

• Drive personalization strategy for eBay recommendations and influence look and feel of the eBay homepage

• Influence how people will interact with recommender systems in the future, and how recommender systems technology will evolve

• Work with unique and large data sets of unstructured multimodal data representing eBay's vast and multifaceted inventory, and millions of users

• Develop and deploy innovative AI models

• Deploy big data technology and large scale data pipelines

• Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations

Qualifications

• MS/PhD in Computer Science or related area with 8 years of relevant work experience (or BS/BA with 10 years) in Engineering / Machine Learning / AI

• Experience leading a nimble engineering/research team, preferably in a ML/AI technology environment

• Experience with using cloud services, big data pipelines and databases

• Experience in Natural Language Processing (NLP) and industrial recommender systems

• Experience in production engineering practices and software development in an OO language (Scala, Java, etc.) and high volume traffic webapp development in an industrial setting

• Previous publications experience with academic papers, patents/IP, or technical blogs is a plus.

Additional Details

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 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.

We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center, and AI Hiring Guidelines.