Open role
Machine Learning Engineer - Agents
eBay International Management B.V.
About the role
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.
Looking for a company that inspires passion, courage and creativity, where you can be on the team shaping the future of global commerce? Want to shape how millions of people buy, sell, connect, and share around the world? If you’re interested in joining a purpose driven community that is dedicated to crafting an ambitious and inclusive work environment, join eBay – a company you can be proud to be with.
Our Search & Recommendations team works on delivering recommendations at scale and in near real time to our buyers on our website and native app platforms. Recommendations are a core part of how our buyers navigate eBay’s vast and varied inventory. Our team develops state-of-the-art recommendations systems, including agentic workflows, deep learning based retrieval systems for personalized recommendations, machine learned ranking models, as well as advanced MLOps in a high volume traffic industrial e-commerce setting.
We are building cutting-edge agentic workflows and next-generation recommendation experiences powered by the latest advancements in LLMs, foundation models, and multi-agent orchestration. We are looking for a Machine Learning Engineer who can develop this effort forward bringing complex, autonomous systems into production at eBay scale. In this role, you will bridge the gap between state-of-the-art research and massive production systems. You will work closely with leaders and globally distributed teams across our Search & Recommendations organization, including product, design, and analytics, to design the mechanics of how multiple intelligent agents collaborate, and reason to enable the future of personalized e-commerce shopping.
What you'll do
Design & Architect Multi-Agent Ecosystems: Build and evaluate robust, multi-step agentic systems on a variety of customer-facing surfaces at eBay, focusing on architectures where multiple agents coordinate, delegate, and communicate to solve complex user intents.
Collaborate with World-Class Experts: Work with a team of applied researchers and engineers with deep expertise in natural language processing, large language models / AI / agentic workflows, recommender systems, and ML production engineering
Advance Orchestration Research: Investigate and implement brand new techniques in agent interaction patterns, including structured communication protocols, reflection loops, evaluator-generator frameworks, and tool-augmented reasoning.
Solve Agentic Scale Challenges: Address unique, frontier challenges inherent to multi-agent production systems, including latency optimization for long-horizon tasks, cost management, safety/guardrails, and handling cascading failures.
Drive Marketplace Impact: Work with unique, massive datasets of unstructured, multimodal inventory data to move core marketplace metrics (GMB) through thorough A/B testing of autonomous user experiences.
What you'll bring
MS/PhD in Computer Science or related area.
5+ years relevant work experience in Machine Learning / AI / ML Engineering
Demonstrated experience researching, building, or studying systems where multiple agents interact, exchange information, critique reasoning, and coordinate decisions over time (e.g., ReAct, tool-calling loops, planning systems).
Extensive development experience, preferably in a ML/AI technology environment (Python, PyTorch, etc.)
Experience with using cloud services, big data pipelines and databases in an industrial setting
Experience in Natural Language Processing (NLP) and industrial recommender systems
Links to some of our previous work: RecSys 2025 paper
Tech Blog 2025 (GenAI Agentic Platform)
Google Cloud Blog 2024
eBay Tech Blog 2022
RecSys 2021 paper