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We are seeking a Senior Machine Learning Engineer who is an expert in Optical Character Recognition (OCR), Natural Language Processing (NLP), Large Language Models (LLMs), and other deep learning models.
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This high performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence as well as robotic process automation (RPA.
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To join our team in Washington, DC. In this role you will work across our client engagements, providing expertise in machine learning algorithms, natural language processing (NLP), data collection, data analysis, data mapping, data profiling, data mining, data modeling, and data visualization.
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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, including Data Science and Machine Learning. where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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The Leidos EW Division performs on programs that include advanced signal processing, machine learning, optimization, detection & estimation, deep learning, and adaptive decision and control.
$65,000 - $117,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As the Data Scientist, your skillset will create useful and actionable insight for the customer through the development of machine learning, deep learning models, and related algorithms.
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Subject matter expertise in one or more of the following: Artificial Intelligence (AI), Natural language Processing (NLP), Machine Learning (ML), Statistical Models, and Text Analytics on large data sets.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
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We are looking for machine learning experts with strong experience in Deep Learning that want to be part of a team that has an opportunity to make a significant impact. At Deloitte, we are creating a world-class Artificial Intelligence and Machine Learning (AI/ML) Center of Excellence to enhance Deloitte’s existing services and empower our clients to gain exponential value from their data.
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Market leader in Digital Transformation & Automation using Artificial Intelligence and Machine Learning. One or more of the following professional certifications: GNFA, GCIH, GCIA, GSEC, CASP+, CySA+, PaLMS, FedVTE.
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As a Data Scientist at our client, you will play a crucial role in developing and implementing state-of-the-art machine learning models for use cases in traffic safety, mobility, and city planning.
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The Senior Lead Data will be responsible for partnering with Technology, Machine Learning, Product Architecture, and other Capital One teams to support the development of the Finance Tech Data Strategy into products and services we create and consume.
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Experience and/or proficiency in Machine Learning, Artificial Intelligence, and/or Natural Language Processing. Experience developing and delivering technology in at least two of the following areas: data analytics, machine learning, data visualization, geospatial analysis, web services, or database development.
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Manager, Cyber Risk & Analysis (Machine Learning) Professional security or risk management certifications, [Certified Risk Management Assurance (CRMA), Certified Regulatory Compliance Manager (CRCM), Certified Information Systems Security Manager (CISSM), Certified Information Security Manager (CISM), Certified Information Systems Security Professional (CISSP), Certified Information Systems Auditor (CISA), or Certified Risk & Information Systems Control (CRISC.
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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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machine learning jobs Title: electrical engineer in Mclean, VA
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