Senior Applied Scientist

eBay • Bellevue, WA

4d

About The Position

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. Senior Applied Research Scientist – Shipping Science At eBay, we are more than a global ecommerce leader—we’re redefining how the world connects to buy, sell, and grow. Our platform empowers millions of buyers and sellers across more than 190 markets, and we’re dedicated to building innovative, scalable AI solutions that power global commerce. Join the Shipping Science team to shape the future of delivery and cost optimization. We are looking for a Senior Applied Research Scientist who combines deep technical expertise, hands-on leadership, and a bias for action to deliver cutting-edge solutions that directly impact eBay's shipping experience. About the Team The Shipping Science team develops advanced AI and machine learning solutions to: - Improve and extend our deep learning architecture for delivery time estimation. - Enhance shipping cost estimation through item attribute inference (e.g., weight and dimensions from textual listing data). - Optimize end-to-end shipping cost efficiency and user experience by integrating modeling insights with business cost structures.

Requirements

• 7+ years of experience in applied machine learning, AI systems, or data-intensive software engineering.
• Strong proficiency with Python, PyTorch, PySpark, and ML frameworks such as scikit-learn, XGBoost, and LightGBM.
• Proven experience building and optimizing deep learning models (e.g., BERT, T5, CLIP, diffusion models) at scale.
• Deep understanding of data pipelines, distributed computing, and performance optimization.
• Hands-on experience with MLOps tools such as Docker and Kubernetes.
• Strong mathematical and statistical foundation, with the ability to connect modeling rigor to business impact.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Nice To Haves

• PhD preferred but not required

Responsibilities

• Lead the research and development of scalable machine learning and deep learning solutions across delivery and cost estimation problems.
• Design, build, and deploy PySpark-based ETL and model training pipelines for production-scale systems.
• Drive rapid prototyping and experimentation of new modeling ideas using architectures such as Transformers, BERT, GPT, and other foundation models.
• Apply advanced ML and AI techniques including RAG, agentic frameworks, and PEFT methods to enhance model performance and flexibility.
• Containerize, deploy, and monitor production-grade models using tools such as Docker, Kubernetes, and internal MLOps platforms.
• Collaborate closely with data engineers, MLOps teams, and product managers to translate business goals into measurable AI-driven outcomes.
• Mentor and guide team members, promoting a culture of ownership, curiosity, and high technical rigor.

Benefits

• The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave).
• Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level