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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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Evaluate commercial and open-source techniques in Machine Learning, Data Mining, NLP, and Analytics. Master's degree in Computer Science, Statistics, or Mathematics required with emphasis on data mining, NLP, or machine learning.
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In this role, you will leverage your expertise in Python, Natural Language Processing (NLP) techniques, algorithms and statistics, as well as your familiarity with US Department of Defense mission needs, to deploy, optimize, and evaluate innovative machine learning and algorithmic solutions in client environments.
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10 or more years of practical working experience in one or more of the following areas: Natural Language Processing, Machine Learning Models, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Data Science, Knowledge Engineering.
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Machine Learning Engineers at CoStar play an important role in this process, by mining data from sources including billions of pageviews, millions of images, vast geographic data, deep property content, and much more.
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Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc.
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As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications.
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Center 3 (19075), United States of America, McLean, VirginiaManager, Cyber Risk & Analysis (Machine Learning) Capital One’s commitment to Machine Learning has sponsorship from leadership and the Enterprise ML Program is at the heart of this effort, and is leading the way towards building responsible and impactful tools, platforms, and solutions that leverage ML and Generative AI.
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Draw on deep technical knowledge and subject matter expertise to advise clients in multiple areas, including clinical psychology, psychiatry, neuroscience, and psychometrics, with an eye toward applications, such as digital mental health, psychological wellbeing, and predictive analytics and machine learning for personalized medicine and prevention.
$150Full-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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We are looking for a Senior Quantitative Scientist with data science, machine learning, and natural language processing (NLP) expertise that will work closely with clinical structured and unstructured text data derived from electronic health records in support of Verana Qdata development which enables insight generation.
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They also use and advise on such tools as machine learning, natural language processing, web scraping, big data platforms, and data visualization techniques and their application to relevant public policy issues.
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Komatsu supports a myriad of markets, including housing, infrastructure, water, pipeline, minerals, automobile, aerospace, electronics, and medical, through its many brands and subsidiaries, including Joy, P&H, Montabert, Modular Mining Systems, Hensley Industries, NTC, and Gigaphoton.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
$174,000 - $218,000 a yearFull-timeExpandApply NowActive JobUpdated 29 days ago - UpvoteDownvoteShare Job
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Knowledge, skills, and relevant experience in one or more of the following is required: - Designing and implementing machine learning - Data mining - Advanced analytical algorithms - Programming - Data science - Advanced statistical analysis - Artificial Intelligence - Computational science - Software engineering - Data engineering.
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Create cyber threat intelligence conclusions by using data science and analysis (e.g. outlier detection, gap analysis, normalization, machine learning, automated models, natural language processing, etc.
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machine learning mining jobs Title: machine learning scientist in Washington, DC
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