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.
About the team and the role:
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.
eBay’s Ads teams build the production systems that help buyers discover relevant inventory and help sellers grow their businesses. These systems span multiple applied ML domains, including sponsored search, item recommendations, seller guidance experiences, ranking, retrieval, personalization, and GenAI-powered capabilities.
As a Senior Backend Engineer, ML Systems you will help build the platforms, services, APIs, data pipelines, and MLOps capabilities that bring cutting edge AI models into production at eBay scale. You will engineer the data pipelines that feed our models, build the infrastructure to train and serve them, and develop the APIs that deliver personalized experiences to millions of users. You will work at the intersection of machine learning and software engineering, solving complex challenges in system design and the operationalization of the latest Generative AI technologies. You will partner closely with Applied Researchers, Product Managers, and cross-org Engineering teams to turn prototypes into robust, scalable, low-latency systems for millions of customers.
This is a shared hiring role across Ads teams. Final team placement will be determined after offers based on each candidate’s experience, strengths, and fit with the needs of Ads Recommendations, Ads Search, and Ads Guidance.
What you will accomplish:
Design, build, and operate scalable backend and ML systems supporting sponsored experiences, ranking, retrieval, and personalization.
Develop and own the MLOps pipelines for continuous integration, continuous delivery (CI/CD), training, validation, and monitoring of all production-grade models.
Engineer robust data pipelines using big data technologies to process vast datasets for model training and feature engineering.
Implement and optimize both traditional ML models and state-of-the-art Generative AI models (including LLMs) for low-latency serving and high-throughput environments.
Collaborate closely with Applied Researchers to translate novel algorithms and research prototypes into hardened, production-ready code.
Champion software engineering best practices, including code reviews, testing, and documentation, within the machine learning team.
Monitor system performance, identify and resolve production issues, and continuously improve the reliability and efficiency of our ML services.
Mentor other team members through code reviews, technical guidance, architecture design, and pair programming.
What you will bring:
MS in Computer Science or related area with 5+ years of relevant work experience (or BS/BA with 7+ years) in ML / AI / Data Engineering.
Expert in production engineering practices and software development in an OO language (Scala, Java, Python, etc.).
Extensive experience in big data distributed processing frameworks, e.g. Apache Hadoop, Spark, Flink.
Experience with ML frameworks like TensorFlow and PyTorch from a production perspective. Experience with serving frameworks (TensorFlow Serving, TorchServe, NVIDIA Triton) and libraries for LLM operations (LangChain, Hugging Face Transformers) preferred.
Proven ability to build and manage CI/CD pipelines for ML models, including proficiency with containerization (Docker, Kubernetes).
Experience with using cloud services, big data pipelines and databases, e.g. AWS, GCP, Azure.
Proven ability to design and build scalable, distributed systems and expose their functionality through well-designed RESTful or gRPC APIs.
A masterful understanding of the challenges and requirements of running machine learning in a live, 24/7 production environment, including monitoring, alerting, and incident response.
Links to some of our previous work:
How eBay Created a Language Model With Three Billion Item Titles
Complementary Item Recommendations at eBay Scale
Transforming Fashion Discovery in E-Commerce through Theme-Based Categorization with GenAI
Scroll into the Future: How eBay’s Multi-Arm Bandits Elevate Product Recommendations Through Dynamic Pagination
Improving eBay’s Fashion Fitment Using Size Signals From Search Queries
Additional Details
eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at [email protected]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
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Skills Required
- Master’s degree in Computer Science or a related field with 5+ years of relevant ML, AI, or Data Engineering experience
- Bachelor’s degree with 7+ years of relevant ML, AI, or Data Engineering experience as an alternative to a master’s degree
- Production engineering and software development experience in an object-oriented language such as Scala, Java, or Python
- Extensive experience with distributed big data processing frameworks such as Apache Hadoop, Spark, or Flink
- Production experience with machine learning frameworks such as TensorFlow or PyTorch
- Experience building and managing CI/CD pipelines for machine learning models
- Proficiency with Docker and Kubernetes
- Experience using cloud services, big data pipelines, and databases, including AWS, GCP, or Azure
- Ability to design and build scalable distributed systems and expose functionality through RESTful or gRPC APIs
- Strong understanding of operating machine learning systems in 24/7 production environments, including monitoring, alerting, and incident response
- Experience with model serving frameworks such as TensorFlow Serving, TorchServe, or NVIDIA Triton
- Experience with LLM operations libraries such as LangChain or Hugging Face Transformers
eBay Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about eBay and has not been reviewed or approved by eBay.
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Healthcare Strength — Medical, dental, and vision coverage begin on the date of hire, complemented by mental health resources, an EAP, disability coverage, FSAs, and wellness initiatives.
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Leave & Time Off Breadth — A robust mix of PTO, paid holidays, flexible work styles, parental leave, and a four‑week paid sabbatical after five years supports work‑life balance.
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Equity Value & Accessibility — Total compensation commonly includes stock components, with access to an employee stock purchase plan at a discount and stock awards enhancing overall packages.
eBay Insights
What We Do
eBay Inc. is a global commerce leader that connects millions of buyers and sellers around the world. We exist to enable economic opportunity for individuals, entrepreneurs, businesses and organizations of all sizes. Our portfolio of brands includes eBay Marketplace and eBay Classifieds Group, operating in 190 markets around the world. We offer sellers the ability to grow a business with little barrier to entry regardless of size, background or geographic location. We never compete with our sellers. We win when our sellers succeed. Buyers who shop on our Marketplace and Classifieds platforms enjoy a highly personalized experience with an unparalleled selection at great value.
