MTS-2 Machine Learning Engineer

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 teams build the production systems that help buyers discover relevant inventory and help sellers grow their businesses. These systems span multiple applied ML domains, including sponsored search, item recommendations, seller guidance experiences, ranking, retrieval, personalization, and GenAI-powered capabilities.

As a Machine Learning Engineer, you will help build the platforms, services, APIs, data pipelines, and MLOps capabilities that bring cutting edge AI models into production at eBay scale. You will engineer the data pipelines that feed our models, build the infrastructure to train and serve them, and develop the APIs that deliver personalized experiences to millions of users. You will work at the intersection of machine learning and software engineering, solving complex challenges in system design and the operationalization of the latest Generative AI technologies. You will partner closely with Applied Researchers, Product Managers, and cross-org Engineering teams to turn prototypes into robust, scalable, low-latency systems for millions of customers.

This is a shared hiring role across Ads teams. Final team placement will be determined after offers based on each candidate’s experience, strengths, and fit with the needs of Ads Recommendations, Ads Search, and Ads Guidance.

What you will accomplish:

- Design, build, and operate scalable backend and ML systems supporting sponsored experiences, ranking, retrieval, and personalization.