# Machine Learning Engineer - Advertising
Join eBay's Advertising team, one of the fastest-growing areas in the company, to help define the future of ecommerce advertising.
## About the Role
You will contribute significantly to designing machine learning models and algorithms that power eBay's advertising systems. The team builds end-to-end ML and data-driven advertising systems for ad serving and advertiser-side optimization, developing sophisticated recommendation models and intelligent, automated mentorship systems using advanced machine learning techniques including GenAI.
## What You Will Accomplish
- Lead End-to-End ML Systems at Scale: Architect, build, and evolve large-scale machine learning systems powering ad ranking, recommendations, and advertiser optimization, with ownership over system design, reliability, and long-term technical direction.
- Drive Strategic, Data-Informed Decisions: Leverage large-scale production data to identify high-impact opportunities, define ambiguous problem spaces, and influence product and business strategy through data-driven insights.
- Own and Elevate the ML Lifecycle: Set best practices across the full ML lifecycle—feature engineering, model development, evaluation, deployment, and monitoring—while improving robustness, reproducibility, and scalability of production pipelines.
- Collaborate Across Functions to Shape Solutions: Partner closely with product, engineering, and research to translate complex business objectives into scalable ML solutions.
- Optimize System Performance at Scale: Define, own, and evolve key system metrics (relevance, revenue, latency, reliability). Lead efforts to improve system efficiency, scalability, and cost-performance tradeoffs.
- Advance ML Innovation in Production: Drive adoption of state-of-the-art approaches (deep learning, GenAI, LLM-based systems) and translate modern technology into practical, high-impact production systems.
- Provide Technical Leadership and Mentorship: Mentor engineers, lead design reviews, and set engineering standards.
## What You Will Bring
- Master's or PhD in Computer Science, Software Engineering, Mathematics, or a related field
- Experience building and scaling production-grade ML systems with a strong track record of delivering impactful solutions in complex environments
- Proven ability to design, deploy, and operate large-scale ML systems, including pipelines, online services, and experimentation frameworks
- Expertise in data structures, algorithms, and distributed system design
- Strong coding skills in Python, Scala, or similar languages
- Hands-on experience with modern ML frameworks and large-scale data processing tools
- Exceptional ability to analyze large datasets and translate findings into actionable improvements
- Strong SQL skills and experience with experimentation and segmentation
- Excellent communication skills with the ability to articulate complex technical concepts and influence partners