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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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Experience with BI Visualization tools, including Qlik Sense, Tableau, or Power BI. As a data scientist, you’re excited at the prospect of unlocking the secrets held by a data set, and you’re fascinated by the possibilities presented by IoT, machine learning, and artificial intelligence.
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Experience with Microsoft SQL Server and Microsoft Power BI, or other data visualization tools such as Tableau. Lead the design and development of dashboards, visualizations, and insights using Microsoft Power BI, Microsoft Excel, and other tools as necessary.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 3+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service.
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This position requires expertise in a variety of analytical and database warehousing and reporting software, including Microsoft Excel, software expertise in SQL report writing, Cognos, Qlik, Microsoft Power BI, and similar business reporting tools software.
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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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Extensive experience or knowledge of data visualization technologies such as Tableau, Power BI, Qlik and Spotfire. Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep.
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Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
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Basic knowledge of deep learning frameworks and algorithms. Experience with machine learning and neural network frameworks on GPUs in Linux. Power Efficiency: Work on power management techniques to optimize GPU power consumption, ensuring efficient operation on both mobile and desktop Linux platforms.
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Hands-on experience with technology such as sensors and signal processing, machine vision and machine learning, and internet-of-things type technology. Knowledge of autonomous sensor deployment and AI-driven machine vision.
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Provide technical expertise and guidance in AI/ML algorithms, data modeling, data engineering, and data governance and support the deployment across various domains (e.g., natural language processing, computer vision, predictive analytics.
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Demonstrated experience in Microsoft 365 and Microsoft Power Platform (PowerApps, Power Automate, and Power BI), and SharePoint Online architecture. They will have extensive expertise in Microsoft InfoPath, Microsoft PowerApps, Microsoft PowerBI, Microsoft Power Query, Canvas Apps, and other compatible SharePoint tools and have a deep understanding of SharePoint governance processes, agile methodologies, and excellent communication skills to collaborate effectively with stakeholders at all levels.
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Leidos is looking for a highly skilled Graphics Processing Unit (GPU) Engineer with a deep understanding of operating systems, hardware, and extensive knowledge of the GPU industry, particularly in the context of Linux-based systems.
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GPU Architecture and Design: Collaborate with a multidisciplinary team to define, develop, and optimize GPU architectures, ensuring they meet stringent performance, power efficiency, and feature requirements.
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Continuously assess and enhance power efficiency strategies. An IAT Level III certification would also be acceptable (CASP+, CCNP Security, CISA, CISSP, GCED, GCIH, CCSP). Proficiency with automation tools such Ansible, Puppet, Salt, Terraform, etc.
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