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The candidate will also provide quantitative/qualitative analysis of technologies as well as serving as Subject Matter Expertise in technical areas of Artificial Intelligence (AI)/Machine Learning, Intelligence, Surveillance and Reconnaissance (ISR) & Electromagnetic Warfare (EW), Space and Stratosphere, Information Operations, Hypersonics, and/or Demonstration and Experimentation.
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Senior Machine Learning Scientist - Microscopy/Biology (Lead)- Hybrid - Ann Arbor, MI page is loaded. Working knowledge of either machine learning management systems such as Azure ML, machine learning workflow-engines such as MLFlow/Airflow/Metaflow, or data storage, databases, and structure for large data volumes.
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Under the supervision of the VP Information Technology, the Technology Learning Manager provides mid-level project management and solutions services in support of Technology Tools Learning, Special Project Workflow, and Business Operations Learning.
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Experience with big data analytics, machine learning, artificial intelligence, or anomaly. As a Sr Cyber Engineer and assured, compliance, assessment, and solution (ACAS) SME on our team, you’ll be able to work individually or in a small integrated team, and lead a task, project.
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Machine Learning: Proficient in machine learning techniques, including supervised and unsupervised learning, deep learning, computer vision, and natural language processing.
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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. Build machine learning platform with multiple types of ML capabilities in Cyber context, including anomaly detection, supervised learning, graph, generative AI, etc.
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The Local, Faith-based, and Transformative Partnerships Hub, within USAID’s Bureau for Development, Democracy, and Innovation (DDI/LFT), is seeking a Monitoring, Evaluation, and Learning Specialist to provide support to the programs under its Locally Led Development Initiatives (LLDI.
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These are difficult hands-on engineering challenges that integrate biophysics, image processing, deep learning, novel electronics, ultrasound, and real-time signal processing that can only be solved with a tight-knit multidisciplinary team.
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Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR.
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As a machine learning engineer, you'll train, test, deploy, and maintain models that learn from data. As an experienced engineer, you know that machine learning (ML) is critical to understanding and processing massive datasets.
$96,600 - $220,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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3+ years of hands-on experience with machine learning model implementation & deployment, especially on clinical notes. 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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Strong engineering experience with the following core platforms and services:VMware ESXi and vSphereMicrosoft Windows Server and Deployment and AdministrationMicrosoft Windows 10 Deployment and Administration DNS, DFS, and DHCPActive Directory and defining, implementing, and maintaining Group Policy Microsoft SCCM with Operating System Deployment (OSD)Data center networking fundamentals (experience with software defined data center networks a plus.
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Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Our diverse workforce includes skilled tradespeople; artificial intelligence, machine learning (AI/ML) experts; engineers; technologists; scientists; logistics experts; and business administration professionals.
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Work with strategic analytics, data science, and data engineering personnel to evaluate and implement emerging solutions such as machine learning, artificial intelligence, and predictive analytics.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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deployment machine learning jobs Title: platform engineer Company: Red Hat in Falls Church, VA
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