Conducting experiments on state-of-the-art machine learning models using Tensorflow for real world, large scale problems; Constructing and enhancing data pipelines for model training and serving using Google cloud products such as Apache Beam/Dataflow, BigQuery, and BigTable; Building machine learning productivity tools (e.g. model quality measurement), deploy them in Kubernetes, and help model engineers adopt them
Requirements:
Strong background in data structures and algorithms; Strong coding and problem solving skills; Familiar with distributed systems and/or databases; Fluent with at least one programming language
Text:
Machine Learning Engineer Intern Conducting experiments on state-of-the-art machine learning models using Tensorflow for real world, large scale problems; Constructing and enhancing data pipelines for model training and serving using Google cloud products such as Apache Beam/Dataflow, BigQuery, and BigTable; Building machine learning productivity tools (e.g. model quality measurement), deploy them in Kubernetes, and help model engineers adopt them Strong background in data structures and algorithms; Strong coding and problem solving skills; Familiar with distributed systems and/or databases; Fluent with at least one programming language
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