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In this role, you will be building ultra large scale batch & streaming datasets to support analytics, experimentation and machine learning and helping to drive our self-serve strategy for reporting on-behalf of data scientists and product engineers as we collectively make product better.
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You'll improve search latency and relevancy using large scale data systems and machine learning. You have experience in backend engineering, data infrastructure, search infrastructure or natural language processing/machine learning.
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Whether you join our Statistics, Optimization, or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, etc. Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing.
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Experience with large scale distributed systems, data processing pipelines and machine learning training and serving infrastructure. Prior experience building machine learning systems in production such as enabling data analytics at scale.
Full-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Experience in building large-scale machine learning infrastructure for online recommendation, ads ranking, personalization, search, NLP, etc. Preferred to have knowledge of machine learning, data mining, information retrieval, statistics or natural language processing.
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Experience with distributed large-scale data processing (preferably Apache Spark). As a Senior Software Engineer in the Central AI team, you will build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines.
$206,300 - $305,700 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Working knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data science, full-stack Experience with Big Data Frameworks, such as hadoop, spark, flink, etc.
$194,000 - $355,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Expert-level with search platform, deep learning training/inference platfrom. Experience with scaling and deploying Machine Learning models. Basic understanding of Machine Learning projects lifecycle.
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Experience in big data frameworks (e.g., Spark/Hadoop/Flink), experience in resource management and task scheduling for large scale distributed systems. Job requirements- Experience in leading an engineering team- Experience in developing and deploying large-scale machine learning systems.
$199,500 - $340,100 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.
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We are revolutionizing how shows, movies, and games are produced, pushing technological boundaries to efficiently deliver streaming video at massive scale over the internet, and continuously improving the discovery and personalization of our offerings to our global user base using Machine Learning and data analytics.
$100,000 - $720,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Whether you join our Statistics, Optimization, or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithmsthat power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely on.
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Applies advanced data science, machine learning, and deep learning algorithms necessary to derive insights and develop solutions on enterprise-scale providing a competitive advantage.
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As such, our research spans many Machine Learning areas, including deep learning, search and recommender systems, causal inference, reinforcement learning and bandits, computer vision, computer graphics, natural language processing, and computational advertising.
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