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Experiences related to machine learning, deep learning, NLP, GenAI, distributed training, model hosting,etc. 2+ years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models.
$204,300 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Demonstrate deep knowledge of data integration principles ETL best practices and data governance frameworks with familiarity in machine learning concepts and data preparation techniques.
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Pearson VUE offers a great environment to start or grow your career, we are now hiring for a Part time Test Administrator to join our team in Reston, VA (11150 Sunset Hills) Starting pay is $ per hour + eligible for accrued paid sick time.
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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges. Explore new machine learning and artificial intelligence approaches for automated object detection, feature extraction/target state estimation, multi-source data fusion, and much more.
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Strong understanding of big data analytics , machine learning , and data manipulation techniques in geospatial contexts, providing insights into how emerging technologies can enhance GEOINT capabilities.
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Full Stack Development experience, including experience with Python, Django web applications, REACT web applications or other Javascript frameworks, RESTful API architecture, and incorporating machine learning models into web apps.
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Extensive experience with Azure Data services (Azure Data Lake, Azure Data Factory, Azure SQL Data Warehouse, Data Lake Analytics, HDInsight, Machine Learning, and Stream Analytics). Apply your skills in Azure Cognitive Services, Azure P,aaS, and Machine Learning services.
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Required Technical Skills : Knowledge/experience in one or more of the following:Back-end Development: Experience with Java, PythonFront-end Development: Course or internship experience with UI/UX design concepts and frameworks (CSS/HTML, JavaScript ie Angular, Vue, Reacts)Experience with data engineering or machine learning technologies.
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Experience with International Financial Reporting Standards (IFRS), Comprehensive Capital Analysis and Review (CCAR) Dodd-Frank Act Stress Test (DFAST) or Current Expected Credit Loss (CECL) standards.
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The SDS should have expertise and/or experience in implementing deep learning or artificial intelligence (AI) projects in a High-Performance Computing (HPC) environment; and will be experienced in working with federal government categorical data from flat files, data warehouses, and external/academic sources, and should demonstrate experience as a data scientist and/or machine learning engineer.
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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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IBTCI specializes in monitoring, evaluation, research, and learning (MERL) and institutional support across many areas and sectors including, but not limited to, conflict and crisis, democracy and governance, agriculture, economic growth, food security, education, environment, and global health.
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Responsibilities include design, embedded software development with unit test via simulation drivers or with mocked hardware, application, and/or processing algorithms, software and hardware system integration, troubleshooting, re-factoring, hands-on build and test, field operations and maintenance, training, and production activities.
$153,600 a yearFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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Expertise implementing machine learning models into cloud native environment and utilizing containerization platforms such as AWS Cloud Containerization services, Docker, and others. What you'll do: Provide TS/SCI machine learning model integration into R&D environments Install, configure, and maintain Linux servers while ensuring system performance, security, and stability.
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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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