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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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Should be dry lab cancer research leveraging computational biology, data science, and machine learning. biostatistics, computer science, physics, data science and machine learning, or similar field, with interest.
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Essential Duties and Responsibilities Architect OpenVPX DSP systems using Annapolis Micro Systems products for applications such as Electronic Warfare (EW), Signals Intelligence (SIGINT), Synthetic Aperture Radar (SAR), Software Defined Radio (SDR), Artificial Intelligence (AI), Machine Learning (ML), and Digital Beamforming (DBF.
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The Business Intelligence Analyst is also a member of CreditXpert's Data Analytics Program (DAP), an innovative, proprietary framework for developing new statistical and machine learning models and advanced products for partners and consumers.
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Knowledge of machine learning techniques for computer vision, and natural language processing. Are you fascinated by the possibilities presented by machine learning and artificial intelligence advances.
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Knowledge of Statistical Analysis, Machine Learning and Deep Learning (NLP) preferred. Including governance, oversight, and execution of the Firm's Anti-Money Laundering (AML), Sanctions, Anti-Corruption and Government and Political Activities Compliance programs.
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We are in search of a Battery Computational Scientist Lead with expertise in Density Functional Theory (DFT), Molecular Dynamics (MD), and/or Machine Learning (ML) to join our dynamic team.
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Our spacecraft technologies help our civilian space and national security space sponsors reason about multiple new technologies including space-based networking, machine learning, cyber security, and image recognition.
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The Director will work to maintain the Institutes position as the disciplinary and intellectual foundation of AI research within the University, enabling MINDS to contribute to and benefit from the success of significant institutional investment in data science, artificial intelligence, and machine learning more broadly, including potential applications to key societal problems such as healthcare and scientific endeavors such as vision, linguistics, and neuroscience.
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Experience in Artificial Intelligence, Data Science, Machine learning, Big Data with emphasis on computational skill sets for research is desirable. The Center aims to study and support research into emerging technological, socio-behavioral, and attitudes towards eSports, sports wagering, problem gambling and business development trends to inform esports and gaming public policy and regulation.
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Relevant experience must be in one or more of the following (for Entry level) but in two or more for Full Performance, Senior, and Expert levels: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, computational science, software engineering, or data engineering.
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Demonstrated experience with open-source computer vision and machine learning libraries (e.g., OpenCV, TensorFlow, and Caffe), Unix/Linux operating systems, and multi-threaded/parallel computing.
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Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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The central proposition is leveraging Artificial Intelligence and Machine Learning to create a quick and reliable analysis and alert system that provides rapid detection across multiple internet sources, precise threat analysis, and prompt resolution with minimal human intervention.
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New York City (Hybrid On-Site): $138,500 - $158,100 for Machine Learning Engineer. At least 1 year of Machine Learning experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
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machine learning jobs in Baltimore, MD
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