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Experience with Digital Engineering, Machine Learning and Artifi cia l Intelligence, Sof tware Development, Solid-state Electrical Circuit Design, Unmanned Systems Design, Human Factors Engineering, or Fault Tree Analysis.
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CUDA (Compute Unified Device Architecture) /OpenCL (Open Computing Language) Programming: Develop and optimize applications using CUDA or OpenCL, harnessing the full potential of GPU hardware for parallel processing, high-performance computing, and machine learning on Linux platforms.
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AWS Graviton powered instances provide the best price performance and support a wide range of computing workloads including application servers, microservices, high-performance computing (HPC), CPU-based machine learning (ML) inference, video encoding, electronic design automation, gaming, open-source databases, and in-memory caches.
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Key job responsibilities•Lead the development and execution of a comprehensive utilities strategy for AWS data centers for new and Machine learning regions•Manage multiple Utilities, EPC and Owner's Engineers to deliver MV and HV power infrastructure, including negotiations and contracting.
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The School of Technology and Innovation in the College of Business, Innovation, Leadership, and Technology (BILT) at Marymount University invites applications from persons qualified to teach undergraduate and graduate Data Science lecture and hands-on courses on topics that include: Data Science Concepts, Data Analysis, DataOps, Machine Learning, Artificial Intelligence, and more.
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Our team supports all phases of analytic work product development, from the identification of key business questions through data collection and ETL, and from performing analyses and using a wide range of statistical, machine learning, and applied mathematical techniques to delivery insights to decision-makers.
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Strong proficiency in programming languages like Python, R, or SQL.Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Develop and implement machine learning models for tasks such as prediction, classification, and clustering.
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10+ years of hands-on experience in NLP, machine learning, or a related field. We are seeking a Principal Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation.
$309,400 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Employ cutting edge Natural Language Processing (NLP) and Machine Learning (ML) techniques to solve complex natural language problems. Join Accenture Federal Services to do the work you love in an inclusive, collaborative, and caring community, where you can be empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more.
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Position Summary:As a senior machine learning engineer on our team, you will build machine learning capabilities using leading-edge technologies for important and challenging government problems and needs.
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We are seeking candidates with expertise in precision health and informatics, as broadly described above, with a focus on research that includes predictive modeling of health outcomes and optimal therapies, clinical application of artificial intelligence and machine learning, disease surveillance systems for monitoring infectious disease and environmental exposures, bio-health informatics, and integration of basic science research and clinical insights.
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In this role, you'll share your technical expertise, introduce best practices, and use tools like Closure, Scala, Python, and R to develop plans and leading major consulting assignments that include data analytics with machine learning and artificial intelligence.
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Experience with applied machine learning (tree-based methods, ensemble methods, neural networks/deep learning) The Data Scientist is responsible for using advanced statistical, algorithmic, machine learning, data mining and visualization techniques to help advance and complete client projects.
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Usage of Azure Storage ranges drastically - from hot access such as disks, to millisecond access such as video streaming data, to cold data such as archival data, and to hyperscale access, big data, machine learning, and many more.
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These teams are made up of other software team members and subject matter experts from the areas of systems engineering, hardware, firmware, machine learning, RF front end design, and signal processing.
$117,500 a yearFull-timeExpandApply NowActive JobUpdated 25 days ago
on machine learning jobs in Arlington, Parkville, Maryland
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