eBay
Manager - ML/Applied Research
Toronto
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About the role
- We're committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.
- Additional Details This job posting relates to an existing vacancy within 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, and disability, or other legally protected status.
Requirements
- If you have a need that requires accommodation, please contact us at talent@ebay.com.
- We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process.
Nice to have
- They also specialize in large language models, AI, recommender systems, and ML production engineering.
- Influence how people will interact with recommender systems in the future, and how recommender systems technology will evolve
- Work with unique and large data sets of unstructured multimodal data representing eBay's vast and multifaceted inventory, and millions of users
- Deploy big data technology and large scale data pipelines
- Experience leading a nimble engineering/research team, preferably in a ML/AI technology environment
- Experience with using cloud services, big data pipelines and databases
- Experience in Natural Language Processing (NLP) and industrial recommender systems
- Experience in production engineering practices and software development in an OO language (Scala, Java, etc.) and high volume traffic webapp development in an industrial setting
Company info
- At eBay, we're more than a global ecommerce leader - we're changing the way the world shops and sells.
- 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.
This listing is sourced directly from eBay's careers page and normalized into a canonical job model.