Senior Applied Researcher

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.
• 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 problem-solving skills and ability to work independently in ambiguous technical areas.
• Excellent collaboration and communication skills, with experience working across research, development, product, and infrastructure groups.
• A strong sense of ownership and a proven history of delivering high-impact applied research work as an individual contributor.
• A track record of applied research impact, such as publications, patents, shipped model improvements, productionalizing research, or measurable product and business outcomes.

What you'll be doing:

• Research, develop, and validate machine learning and Generative AI capabilities for large-scale ecommerce applications.
• Define and complete applied research agendas in various areas related to foundation models.
• Develop novel modeling approaches, training methods, and evaluation frameworks for foundation model-powered ecommerce experiences.
• Build evaluation methodologies to measure model quality, robustness, and customer impact.
• Develop learning systems that improve from feedback signals.
• Analyze model behavior, failure modes, and data patterns to propose improvements.
• Collaborate with machine learning engineers and platform teams to transform research prototypes into production capabilities.
• Work with various teams to incorporate AI capabilities into eBay experiences.
• Stay current with advances in machine learning, Generative AI, and foundation models.
• Raise scientific and technical standards through structured experimentation and technical contributions.
• Contribute to publications, patents, research reviews, and technical strategy as needed.

Perks and Benefits:

• Not specified in the job description.