Coupang is seeking a Staff Machine Learning Engineer for the Search & Discovery team in Mountain View, California. This on-site role focuses on building scalable offline and online ML platforms to support ranking, recommendation, and business decision making. You will process billions of user interactions and petabytes of log data, transforming them into data objects that engineers and scientists can use, and you will deploy real-time ML models to help millions of customers search and discover products. Responsibilities include designing features and large-scale ML models to improve relevance, ranking, personalization, and engagement; building ML systems for search ranking, semantic retrieval, query understanding, and personalized discovery using transformer-based models, contrastive learning, and vector search; advancing search relevance and user intent modeling using large language models (LLMs), embeddings, and multi-modal learning; building and optimizing ML pipelines with Apache Spark, Airflow, Kubeflow, and MLflow with a focus on reproducibility and operational excellence; defining and tracking KPIs to measure impact and identifying opportunities for improvement; collaborating cross-functionally with product, engineering, and data science teams; mentoring engineers and fostering a culture of technical excellence and continuous learning. Basic qualifications include a Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields, and at least four years of professional experience in applied machine learning, with profi

Coupang is seeking a Staff Machine Learning Engineer for the Search & Discovery team in Mountain View, California. This on-site role focuses on building scalable offline and online ML platforms to support ranking, recommendation, and business decision making. You will process billions of user interactions and petabytes of log data, transforming them into data objects that engineers and scientists can use, and you will deploy real-time ML models to help millions of customers search and discover products. Responsibilities include designing features and large-scale ML models to improve relevance, ranking, personalization, and engagement; building ML systems for search ranking, semantic retrieval, query understanding, and personalized discovery using transformer-based models, contrastive learning, and vector search; advancing search relevance and user intent modeling using large language models (LLMs), embeddings, and multi-modal learning; building and optimizing ML pipelines with Apache Spark, Airflow, Kubeflow, and MLflow with a focus on reproducibility and operational excellence; defining and tracking KPIs to measure impact and identifying opportunities for improvement; collaborating cross-functionally with product, engineering, and data science teams; mentoring engineers and fostering a culture of technical excellence and continuous learning. Basic qualifications include a Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields, and at least four years of professional experience in applied machine learning, with profi