Requirements

Master’s, PhD, or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, or related field with 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
Proven proficiency in software development with Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar
Experience working with scalable data processing, distributed systems, cloud infrastructure, or model-serving platforms
Ability to design practical solutions that balance quality, latency, cost, reliability, and maintainability
Strong problem-solving skills and ability to work independently in ambiguous technical areas
Excellent collaboration and communication skills, with experience working across research, engineering, product, and platform teams
A strong sense of ownership and a track record of delivering high-impact technical work as an individual contributor

What You'll Be Doing

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 strong software engineering practices, including code quality, testing, monitoring, documentation, and operational excellence
Know the latest advances in machine learning, Generative AI, and foundation models, and help bring relevant innovations into production
Raise scientific and technical standards through structured experimentation, peer review, documentation, and thoughtful technical contributions