Senior Manager, Applied Research

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:

Looking for a company that inspires passion, courage and creativity, where you can be on the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you’re interested in joining a purpose driven community that is dedicated to crafting an ambitious and inclusive work environment, join eBay – a company you can be proud to be with.

eBay’s Ads AI organization builds intelligent systems that help buyers find what they want and help sellers connect with the right customers. The organization brings together applied research, machine learning engineering, product, analytics, and platform teams working across multiple ads and marketplace discovery experiences.

As a Senior Manager, Applied Research, you will lead a high-performing team of applied researchers and engineers developing production AI systems at eBay scale. You will set technical direction, hire and develop talent, and partner with product, design, analytics, engineering, and business leaders to deliver measurable customer and business impact. This is a shared leadership role across Ads AI teams and will support the needs of Recommendations Ads, Search Ads, and Ads Guidance.

What you will accomplish:

- Lead and manage a team of applied researchers and engineers with deep expertise in natural language processing, large language models / AI, recommender systems, and ML production engineering.

- Set technical direction for production ML systems that improve customer and business outcomes.

- Partner across product, engineering, analytics, design, and business teams to turn ambiguous opportunities into scalable solutions.