Machine Learning Engineer - Depop
Ebay INC · 🇨🇦 Toronto
Sponsorship verdict
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Sponsor Radar — Ebay INC
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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. About the Team As part of this focused C2C strategy, eBay continues to invest in the future of circular commerce and the next generation of conscious consumers. With the recent acquisition of Depop, a leading consumer-to-consumer fashion marketplace with a highly engaged Gen Z and Millennial customer base, eBay is expanding its portfolio of complementary C2C businesses while preserving the distinct brand, community, and product experience that make Depop unique. The Depop team is building intelligent, scalable experiences powered by the latest Machine Learning, AI, NLP, LLM/GenAI, and RAG technologies . We work with large-scale marketplace data and modern ML infrastructure to develop and productionize solutions that improve how millions of buyers and sellers interact with the Depop marketplace. This is an opportunity to: • Influence how AI and Machine Learning shape the future of Depop's global marketplace and customer experience. • Work with large and unique datasets, including structured and unstructured marketplace data representing millions of users and items. • Develop and deploy state-of-the-art AI and ML models into production with direct, measurable impact on buyers and sellers. • Build and scale large data pipelines and distributed systems that support production ML applications. • Partner across engineering, product, data, and applied science teams to take ML solutions from experimentation through production. • Contribute to modern ML infrastructure, deployment, monitoring, and operational best practices at scale. Qualifications • MS in Computer Science or a related field with 5+ years of relevant experience, or BS with 7+ years of relevant experience in Software Engineering, Machine Learning, AI, or a related discipline. • Experience building large-scale distributed applications and proficiency in an object-oriented or modern programming language such as Java, Scala, or Python. • Experience working with NoSQL databases and key-value stores such as MongoDB or Redis. • Experience building and supporting scalable data and ML pipelines. • Strong problem-solving skills with a willingness to learn and adopt new technologies as needed. • Experience with cloud platforms and cloud-native technologies. • Experience with large-scale data processing technologies such as Spark or Hadoop is a plus. • Experience productionizing Machine Learning or AI models and building supporting infrastructure is a plus. • Experience with MLOps, model serving, monitoring, observability, and deployment automation is a plus. • Experience with Large Language Models (LLMs), GenAI, RAG, and prompt engineering is a plus. Additional Details The base pay range for this position is expected in the range below: C$142,400 - C$190,100 Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or