Machine Learning Engineer II
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The role
Design and deploy cutting-edge ML and deep learning solutions to personalize experiences and improve candidate retrieval.
Partner with cross-functional teams to experiment and refine models for Homefeed, Ads, Growth, Shopping, and Search.
Build end-to-end data processing pipelines and large-scale ML systems using big data technologies (e.g., Hadoop/Spark).
Operate in a fast, high-impact environment with rapid experimentation and product launches while keeping up with industry trends.
Work in a hybrid setup with in-person collaboration 1–2 times per quarter and be within commuting distance of the Toronto office.
Requirements: 2+ years of ML experience (personalization, recommender systems, NLP, ranking, etc.), MS/PhD in ML or related field, and real-time streaming data expertise.
Partner with cross-functional teams to experiment and refine models for Homefeed, Ads, Growth, Shopping, and Search.
Build end-to-end data processing pipelines and large-scale ML systems using big data technologies (e.g., Hadoop/Spark).
Operate in a fast, high-impact environment with rapid experimentation and product launches while keeping up with industry trends.
Work in a hybrid setup with in-person collaboration 1–2 times per quarter and be within commuting distance of the Toronto office.
Requirements: 2+ years of ML experience (personalization, recommender systems, NLP, ranking, etc.), MS/PhD in ML or related field, and real-time streaming data expertise.
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