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Whether you join our Statistics, Optimization, Advanced Algorithms 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 Search, Personalization, GenAI, Marketing, Supply Chain Optimization, Network Security rely on.
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Experience working in fields like recommendation systems, natural language processing, applied machine learning, large scale production search/ranking system, large data pipelines and/ or other related systems.
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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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Experience with machine learning/big data at scale (GPU, Docker and Kubernetes) Specific Skillset We're looking to augment our existing team with someone who has deep experience in managing a large Elasticsearch cluster indexing machine learning vectors that power many features in our product including dataset search.
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Qualifications Qualities that will help you thrive in this role are: You have experience developing impactful solutions to machine learning & NLP problems involving some or all of the following parts of the pipeline: data extraction, developing and training machine learning models, working the new model into production applications.
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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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From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
$133,000 - $194,000 a yearFull-timeExpandApply NowActive JobUpdated 30 days ago - UpvoteDownvoteShare Job
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These new experiences are powered by a large-scale deep learning-based enterprise search and question-answering systems built by the team, which processes billions-to-trillions of data items and serves millions of end users in millisecond latency.
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Familiarity with natural language processing and machine learning techniques in the context of search. Dive deep into technical challenges related to scale, ensuring that our search capabilities can handle new indices and mappings with increasing volumes of data and user interactions.
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Experience in one or more of the following areas: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning. Responsible for the research and application of the company's large-scale models, exploring new applications and solutions for related technologies in the fields of search, recommendation, advertising, content creation, and customer service, to meet the growing demand for intelligent interactions from users and comprehensively improve their way of life and communication in the future world.
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Experience working with numerical, scientific, and machine learning libraries is desired. Experience with data transport tools and messaging busses. Work with teams to build data catalogs and track lineage.
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Working experience with several from the following: systems infrastructure, large-scale database implementation and design, machine learning, search engine ranking, and/or web scale data science.
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At this time, they are seeking Machine Learning Engineering Manager where you will own the product road map and scale their AI products and platform. Create highly scalable classifiers and tools utilizing machine learning, data regression, and rule-based models.
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As a member of our team, you will be responsible for developing performant backend retrieval systems while working with machine learning and large language models (LLMs). Curate and manage large-scale data ingestion and indexing pipelines.
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Hydroinformatics - Motivated by the expansion of data acquisition systems and the need for managing and using massive datasets, this position requires specialization in information systems and technology for water management, engineering, and operations, with expertise in extreme data management, analytics, data mining, large dataset access, remote sensing, artificial intelligence, machine learning, water systems modeling, and geographic information systems.
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