Senior Machine Learning Engineer, Personalization & Recommendations
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The role
Design, implement, and optimize large-scale retrieval, ranking, and recommendation pipelines.
Build and deploy Two-Tower models, deep ranking networks, and embedding-based personalization using vector search.
Develop end-to-end ML pipelines for training, evaluation, deployment, monitoring, and drift detection.
Collaborate with product, data science, and platform teams to translate learner goals into measurable modeling objectives and experiments.
Advance evaluation methods with offline metrics (NDCG, AUC, calibration) and rigorous online A/B testing to drive engagement, retention, and mastery.
Mentor junior engineers, promote responsible ML practices, and foster an inclusive, data-driven team culture.
Build and deploy Two-Tower models, deep ranking networks, and embedding-based personalization using vector search.
Develop end-to-end ML pipelines for training, evaluation, deployment, monitoring, and drift detection.
Collaborate with product, data science, and platform teams to translate learner goals into measurable modeling objectives and experiments.
Advance evaluation methods with offline metrics (NDCG, AUC, calibration) and rigorous online A/B testing to drive engagement, retention, and mastery.
Mentor junior engineers, promote responsible ML practices, and foster an inclusive, data-driven team culture.
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