Applied Researcher 2

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:

Our Seller Experience Team is at the forefront of this mission, using groundbreaking algorithms to enhance personalization, recommendation systems, messaging experience, reviews and build trust. We are looking for stellar applied researchers to join us and play a pivotal role in advancing eBay’s seller as well as buyer experience.

What you will accomplish:

1. Lead the design and implementation of sophisticated algorithms to enhance the selling experience and build user trust.
2. Develop machine learning models and scalable data pipelines to deliver practical, data-driven solutions.
3. Stay informed about the latest advancements in algorithms and machine learning, integrating innovative techniques to improve business metrics and user experience.
4. Collaborate with cross-functional teams to transition research insights into production systems, ensuring scalability and performance.
5. Conduct experiments and analyze data to drive continuous model improvements.
6. Communicate research findings and technical concepts effectively to both technical and non-technical stakeholders.

What you will bring:

1. MS or PhD in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience.
2. Extensive industry experience in designing, developing, and deploying machine learning models (minimum 3-5 years with MS or 1-3 years with PhD).
3. Strong expertise in machine learning and data science, with experience in areas such as Generative AI, NLP, recommendation systems, ranking, fraud detection, or online advertising. Passion for applying research to solve real-world challenges.
4. Proficiency in Python, Java, or similar languages, with experience using ML frameworks like TensorFlow or PyTorch. Familiarity with big data tools such as Hadoop, Spark, and SQL.
5. Excellent problem-solving skills and ability to work in a fast-paced environment.
6. Proven track record of publishing research in top-tier conferences or journals is a plus.
7. Experience in e-commerce or a related industry is a plus.