machine learning engineer for ecommerce AI

eBay is a global ecommerce platform that connects buyers and sellers in more than 190 markets. Its Foundation Models team builds Generative AI and foundation-model capabilities for intelligent marketplace experiences, including retrieval, multimodal understanding, and personalization.

• Design, build, and productionalize machine learning and Generative AI capabilities for large-scale ecommerce applications;
• Build and optimize systems involving LLMs, retrieval-augmented generation, embeddings, multimodal models, ranking, and personalization;
• Develop learning systems that improve from feedback signals, including reinforcement learning, preference optimization, reward modeling, bandits, and online/offline feedback loops;
• Partner with applied researchers to turn prototypes and experiments into maintainable production capabilities;
• Build robust training, fine-tuning, evaluation, and deployment pipelines for large-scale machine learning models;
• Improve model quality, latency, cost, reliability, and observability across production AI systems;
• Collaborate with engineering, product, and platform teams to integrate AI capabilities into eBay experiences;
• Apply software engineering practices including code quality, testing, monitoring, documentation, and operational excellence;
• Track advances in machine learning, Generative AI, and foundation models and bring relevant innovations into production;
• Raise scientific and technical standards through structured experimentation, peer review, documentation, and technical contributions.

• Master’s, PhD, or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field;
• 8 Years of relevant work experience;
• Strong hands-on experience building and deploying machine learning systems in production environments;
• Deep understanding of machine learning, NLP, Large Language Models, neural architectures, embeddings, retrieval, ranking, or multimodal modeling;
• Experience with model training, fine-tuning, evaluation, deployment, and performance optimization;
• Experience with reinforcement learning or feedback-driven learning systems, including preference learning, reward modeling, bandits, or continuous model improvement loops;
• Proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar;
• Experience with scalable data processing, distributed systems, cloud infrastructure, or model-serving platforms;
• Ability to design practical solutions balancing quality, latency, cost, reliability, and maintainability;
• Strong problem-solving skills and ability to work independently in ambiguous technical areas;
• Excellent collaboration and communication skills across research, engineering, product, and platform teams;
• Strong ownership and a track record of delivering high-impact technical work as an individual contributor.

• Work location: Amsterdam, North Holland, Netherlands;
• Equal opportunity employer with accommodations available for applicants with disabilities.