Sr MTS Machine Learning Engineer
The role involves building and scaling machine learning models for eBay’s global commerce platform, collaborating with product and data teams. It requires end‑to‑end development from data preprocessing to deployment in a cloud environment.
Skills required
About this role
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 are building the next generation of intelligent marketplace experiences 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 Sr MTS Machine Learning Engineer, you will serve as a senior technical leader for high-impact ML initiatives. You will help set direction, define engineering approaches, guide experimentation, and work hands-on with researchers and engineers to bring ML systems into production. The candidate will work closely with leaders and other teams from our globally distributed Ads organization, including product managers, design, and analytics leaders to brainstorm and enable future personalized e-commerce shopping experiences. This is a shared technical lead role across Ads teams and will support the needs of Recommendations Ads, Search Ads, and Ads Guidance.
What you will accomplish:
Provide technical leadership to a team of engineers for ML initiatives across Ads and marketplace discovery
Champion software engineering best practices, including code reviews, testing, and documentation, within the machine learning team
Design, build, and operate scalable backend and ML systems supporting sponsored experiences, ranking, retrieval, and personalization
Collaborate closely with Applied Researchers to translate novel algorithms and research prototypes into hardened, production-ready code
Mentor other team members through code reviews, technical guidance, architecture design, and pair programming
Drive measurable customer and business impact through disciplined A/B testing and iteration
What you will bring:
MS in Computer Science or related area with 10+ years of relevant work experience (or BS/BA with 13+ years) in ML / AI / Data Engineering.
Expert in production engineering practices and software development in an OO language (Scala, Java, etc.)
Experience using cloud services, big data pipelines, databases, and distributed processing frameworks, e.g. Apache Hadoop, Spark, Flink
Extensive hands-on experience developing production ML/AI systems using Python and modern ML frameworks such as PyTorch and TensorFlow
Experience with serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton) and libraries for LLM operations (LangChain, Hugging Face Transformers) preferred
Proven ability to design and build scalable, distributed systems and expose their functionality through well-designed RESTful or gRPC APIs
A masterful understanding of the challenges and requirements of running machine learning in a live, 24/7 production environment, including monitoring, alerting, and incident response
Links to some of our previous work:
How eBay Created a Language Model With Three Billion Item Titles
Complementary Item Recommendations at eBay Scale
Transforming Fashion Discovery in E-Commerce through Theme-Based Categorization with GenAI
Scroll into the Future: How eBay’s Multi-Arm Bandits Elevate Product Recommendations Through Dynamic Pagination
Improving eBay’s Fashion Fitment Using Size Signals From Search Queries
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 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 for people with disabilities.
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