ml engineer for ecommerce advertising

eBay is a global ecommerce platform that connects millions of buyers and sellers across more than 190 markets. Its advertising initiatives help sellers move inventory, surface high-quality items for buyers, and create economic opportunity through marketplace commerce.

• Architect, build, and evolve large-scale machine learning systems for ad ranking, recommendations, and advertiser optimization, owning system design, reliability, and long-term technical direction;
• Use large-scale production data to identify high-impact opportunities, define ambiguous problem spaces, and influence product and business strategy;
• Set best practices across feature engineering, model development, evaluation, deployment, and monitoring while improving production pipeline robustness, reproducibility, and scalability;
• Partner with product, engineering, and research teams to translate complex business objectives into scalable ML solutions and influence roadmap prioritization;
• Define, own, and evolve system metrics such as relevance, revenue, latency, and reliability;
• Lead efforts to improve system efficiency, scalability, and cost-performance tradeoffs in high-throughput environments;
• Drive adoption of deep learning, GenAI, and LLM-based systems in practical production solutions;
• Mentor engineers, lead design reviews, and set engineering standards;
• Act as a technical anchor for the team and raise the standard of ML engineering excellence and experimentation rigor.

• Master’s or PhD in Computer Science, Software Engineering, Mathematics, or a related field;
• Experience building and scaling production-grade ML systems and 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, with the ability to make high-quality architectural tradeoffs;
• Strong coding skills in Python, Scala, or similar languages;
• Hands-on experience with modern ML frameworks such as PyTorch, Hugging Face, Ray, or vLLM;
• Experience with large-scale data processing tools such as Spark or Hadoop;
• Ability to analyze large datasets, perform deep dives, and translate findings into actionable improvements;
• Strong SQL skills and experience with experimentation and segmentation;
• Excellent communication skills and ability to articulate complex technical concepts, influence partners, and drive alignment across teams.

• Office role in Amsterdam, North Holland, Netherlands;
• No conditions specified.