Job Description

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.


Our Recommendations team works on delivering item 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 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. This role is for engineers who are passionate about bringing sophisticated machine learning and Generative AI models from prototype to production, ensuring they are robust, scalable, and performant.


As a Machine Learning Engineer, you will be the driving force behind building, deploying, and scaling our cutting-edge recommendation-as-a-service platform. You will be responsible for the entire ML lifecycle in a production environment. 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, MLOps, and the operationalization of the latest Generative AI technologies.

This Is An Opportunity To

Design, build, and maintain scalable, production-grade machine learning systems for real-time recommendations and generative services. Develop and own the MLOps pipelines for continuous integration, continuous delivery (CI/CD), training, validation, and monitoring of all recommendation 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. Develop and manage the APIs and infrastructure necessary for serving recommendations and integrating with other systems. 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.

Qualifications

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MS in Computer Science or related area with 3 years of relevant work experience (or BS/BA with 5 years) in ML / AI / Data Engineering Experience in production engineering practices and software development in an OO language (Scala, Java, etc.) 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 deep understanding of the challenges and requirements of running machine learning in a live, 24/7 production environment, including monitoring, alerting, and incident response

Benefits are an essential part of your total compensation for the work you do every day. Whether you're single, in a growing family, or nearing retirement, eBay offers a variety of comprehensive and competitive benefit programs to meet your needs. Including maternal & paternal leave, paid sabbatical, and plans to help ensure your financial security today and in the years ahead because we know feeling financially secure during your working years and through retirement is important.


Here at eBay, we love creating opportunities for others by connecting people from widely diverse backgrounds, perspectives, and geographies. So, being diverse and inclusive isn't just something we strive for, it is who we are, and part of what we do each and every single day. We want to ensure that as an employee, you feel eBay is a place where, no matter who you are, you feel safe, included, and that you have the opportunity to bring your unique self to work. To learn about eBay's Diversity & Inclusion click here:

https://www.ebayinc.com/company/diversity-inclusion/

Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.


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 talent@ebay.com. 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.



The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information.


Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.


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 talent@ebay.com. 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.



The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information.


Please see the Talent Privacy Notice for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.


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 talent@ebay.com. 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.



The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our Privacy Center for more information.