Machine Learning Engineer (T25)

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. Machine Learning Engineer (T25), Product Knowledge This is an opportunity to: Research, develop, and validate machine learning and Generative AI capabilities for large-scale ecommerce applications. Define and complete applied research agendas in areas such as LLMs, retrieval-augmented generation, embeddings, multimodal modeling, ranking, agentic systems, and learning guided by feedback. Develop novel or improved modeling approaches, training methods, adaptation techniques, and evaluation frameworks for foundation-model-powered ecommerce experiences. Build rigorous offline and online evaluation methodologies to measure model quality, robustness, latency, cost, and customer impact. Develop learning systems that improve from feedback signals, including reinforcement learning, preference optimization, value-based modeling, multi-armed bandit algorithms, and online/offline feedback loops. Analyze model behavior, failure modes, and data patterns to identify limitations and propose practical improvements. Develop strong training, fine-tuning, evaluation, and experimentation workflows for large-scale machine learning models. Collaborate with machine learning engineers and platform teams to transform research prototypes into scalable, maintainable production capabilities. Work together with engineering, product, and platform teams to incorporate AI capabilities into eBay experiences. Stay current with advances in machine learning, Generative AI, and foundation models, and assess their relevance through practical experimentation and measurable impact. Raise scientific and technical standards through structured experimentation, peer review, documentation, and thoughtful technical contributions. Contribute to publications, patents, internal research reviews, and technical strategy where appropriate.

6+ years proven work experience in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, or a related field. Extensive direct experience building, analyzing, and refining machine learning models or foundation-model features, preferably involving production or large-scale use cases. Deep understanding of machine learning, NLP, Large Language Models, neural architectures, embeddings, retrieval, ranking, personalization, or multimodal modeling. Experience with model training, fine-tuning, adaptation, evaluation, benchmarking, and performance analysis. Experience with reinforcement learning or learning systems that improve based on input, including preference learning, reward modeling, bandits, or continuous model improvement loops. Strong capability to develop controlled experiments, define meaningful metrics, interpret results, and communicate tradeoffs clearly. Proven proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar. Experience working with large-scale datasets, model training or evaluation pipelines, and collaboration with engineering teams to bring research into production. Ability to formulate ambiguous product or platform problems as concrete research questions and evaluate practical solution paths. Ability to build practical solutions that balance model quality, latency, cost, reliability, and maintainability. Strong