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.

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.

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.

- 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.

- 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 (PhD preferred but not required).

- Bias to Action: Moves quickly from idea to prototype with measurable results.
- Ownership: Takes accountability for outcomes, not just deliverables.
- Curiosity: Constantly explores new modeling paradigms and technologies.
- Collaboration: Works effectively across disciplines to elevate team productivity and innovation.

The base pay range for this position is expected in the range below:

Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. 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.

If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

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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 [email protected]. 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. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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