Senior Applied Scientist

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.

Our Recommendations team works on delivering recommendations at scale and in near real time to our buyers on our website and native app platforms. Recommendations are a core part of how our buyers navigate eBay’s vast and varied inventory. Our team develops state-of-the-art recommendations systems, including deep learning based retrieval systems for personalized recommendations, machine learned ranking models, as well as advanced MLOps in a high volume traffic industrial e-commerce setting.

We are exploring a new generation of recommender systems powered by Large Language Models and other emerging paradigms in GenAI. We are looking for a Senior Applied Scientist and innovator who can drive state of the art ML engineering, define research directions, and get systems into production at eBay scale.

This Is An Opportunity To:

• Build data pipelines needed to support user input, recall and ranking, model training and inference, working with architects and other engineering peers.
• Track the fast paced world of AI and apply innovative techniques to unique and large data sets of unstructured multimodal data representing eBay's vast and varied inventory, and millions of users
• Develop and deploy innovative models in the context of recommender systems
• Deploy big data technology and large scale data pipelines to create magical AI applications and user experiences
• Have real impact on how shoppers interact with one of the world's largest e-commerce marketplaces, find what they love every day
• Drive marketplace GMB as well as advertising revenue via organic and sponsored recommendations

Qualifications

• PhD in Computer Science or related area with 4 years of relevant work experience (or MS with 6 years) in ML / AI / Data Engineering
• Experience in AI applied research, preferably in Natural Language Processing (NLP) and industrial recommender systems
• Experience in production engineering practices as well as big data pipelines and databases
• A high bar for engineering excellence in terms of practices and processes