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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.
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As a Junior Software Engineer, you will support a mission critical program leveraging open-source technologies, AWS cloud compute, services and infrastructure and machine-learning to automate tasks and provide insight for the Department of Defense.
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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. This position may involve access to technology or technical data that is controlled under U.S. export control laws and regulations and the release of which to a foreign national may require an export license from the U.S. Government.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. For technical support or questions about Capital One's recruiting process, please send an email to.
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Cutting-Edge Machine Vision*: We're in the business of AI and data science. Cutting-Edge Machine Vision: We're in the business of AI and data science. Knowledge of autonomous sensor deployment and AI-driven machine vision.
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Certifications and specialization in IT Ops, Infrastructure, APM, Data Engineering, Machine Learning, Data Infrastructure. Lead, hands-on-deploy (from data onboarding, configuration, visualizations, alerting), and seamlessly integrate Elastic products and APIs into intricate platform architectures, harnessing years of technical expertise.
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Incorporate machine learning capabilities to enhance Explosive Ordnance Disposal (EOD) and Recovered Chemical Warfare Material (RCWM) applications to streamline business processes. Incorporate applications that promote machine learning / artificial intelligence.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Data science techniques such as predictive analytics, machine learning, natural language processing and business intelligence, including use of big and non-tabular data. Analysis, design and implementation of country-level health architectures, including knowledge of relevant technical standards for digital health such as ICD10, HL7, SNOMED and OpenHIE.
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Familiarity with additional technologies like Qlik, Tableau, Micro-Services, Web-services, Chatbots, Machine Learning (ML)/deep learning, Natural Language Processing (NLP), Lucene/ElasticSearch.
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As a Senior Associate in our Risk Analytics and Modeling team, you’ll have the opportunity to apply your quantitative, modeling and analytical skills in a real world environment to develop or validate statistical, financial engineering, and AI/machine learning models in the areas of credit risk, market risk, assets and liabilities management, fraud detection, anti money laundering and other functional modeling and analytics area.
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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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Ii) develop of machine learning and computational discovery methods for public health research. Experience in Bioinformatics or Data Science, including independent algorithm/software development and analysis of next-generation microbial sequencing data.
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You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. 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.
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machine learning technical jobs Title: data engineer Company: Amazon in Mclean, VA
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