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Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing. Experience in building large-scale machine-learning infrastructure for online recommendation, ads relevance and/or ranking, personalization, search, or similar area.
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Experience in machine learning, deep learning, information retrieval, knowledge graphs, natural language processing or data mining. MS or PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Machine Learning, Information Retrieval, Data Science or related field.
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Familiar with 1-2 areas in natural language processing, computer vision, multimodal, graph algorithms, search algorithms, text/data mining, and LLM. Solid foundation in data structures/algorithms, proficient in machine learning/deep learning theory, and rich practical experience.
$137,750 - $237,500 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Our clients trust us to use natural language processing (NLP) and machine learning (ML) to deliver experiences like Search, Chat, Local Listings, and pages. Knowledge of unsupervised machine learning and information retrieval and mining (e.g. DBSCAN, k-Means, indexing, BM25, and evaluation metrics in these problems.
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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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Machine learning, recommendation systems, computer vision, natural language processing, data mining, or distributed systems. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow.
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From creating experiments and prototyping implementations to designing new architectures, Research Scientists work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Develop solutions that iterate orders of magnitude with a higher efficiency, efficiently leverage orders of magnitude and more data, and explore state-of-the-art deep learning techniques.
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8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, NLP, data mining or artificial intelligence. Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models.
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The position may bring expertise in related areas of image processing, geospatial and statistical analysis, data fusion, and machine learning. This position requires application of large-scale hydrologic modeling with specialization in high-performance computing, artificial intelligence, machine learning, remote sensing, and cloud computing.
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Adapt standard machine learning methods to best exploit modern parallel environments (e.g. Data processing, programming languages, databases, networking, operating systems, computer graphics, or human-computer interaction.
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Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU) Meta is seeking Machine Learning Engineers to join our engineering team.
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Full text indexing and searching technologies such as Lucene and ElasticSearch, tuning indexing and searching for search relevancy and accuracy; using data mining and machine learning tools and algorithms.
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Knowledge of other Machine Learning techniques such as Natural Language Processing (NLP) and text mining, and Neural Networks is a plus. Working closely with both the Business Planning and Analytics teams, Data Sciences designs and implements statistical models and machine learning solutions that tie our clients’ marketing to real-world business goals.
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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.
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