Senior Machine Learning Engineer

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.

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 reinventing the future of ecommerce for enthusiasts.

The Foundation Models team is at the forefront of this transformation. We are building next-generation Generative AI and foundation-model capabilities that power intelligent experiences across eBay at global scale. From advanced retrieval systems to multimodal understanding, our work directly shapes how customers discover, evaluate, and engage with inventory across the marketplace. We are seeking a Senior Machine Learning Engineer to join our group passionate about Foundation Models as an individual contributor. In this role, you will design, build, and productionalize machine learning systems that bring advanced AI capabilities into real customer-facing and platform experiences. You will work closely with applied researchers, engineers, and product partners to turn state-of-the-art ideas into scalable, reliable, and measurable systems. This is a hands-on technical role for someone who combines strong machine learning expertise with solid engineering judgment and a passion for building production-grade AI systems.

This is an opportunity to: 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

Master’s, PhD, or equivalent experience in Computer Science, Machine Learning, Artificial Intelligence, Computational Linguistics, or a 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 the 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