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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. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in St. Louis, MO.
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Graduate Big Data Analytics Natural Language Processing Machine Learning Data Mining Cybersecurity Cyber-Human Systems. The Department of Information Sciences and Technology (IST) has 44 full-time faculty members with research foci in cybersecurity, data mining and machine learning, natural language processing, human-centered computing, and computing and engineering education.
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We are looking for a Data Scientist with exceptional skill to develop machine learning and deep learning models and algorithms that create useful and actionable insight for customers. 3 or more years of practical working experience in one or more of the following areas: Natural Language Processing, Machine Learning Models, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Data Science, Knowledge Engineering.
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San Francisco and San Jose, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer. Sales Territory or Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer.
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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. Collaborate with data scientists and machine learning engineers to support model development through data preparation and analysis.
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Technical Proficiency: Expertise in Python, machine learning tools (Hadoop, TensorFlow, Apache Spark), and deep learning frameworks. Your innovative approach will harness machine learning and artificial intelligence to deliver impactful solutions, enabling customers to make informed, data-driven decisions through prototypes and scalable production systems.
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Hands-on experience with machine learning (including deep learning and reinforcement learning), and one or more of the following technical areas: large language models (LLM), generative AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ontologies.
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The Senior Manager of Ontology and Data Modeling will be responsible for partnering with Technology, Machine Learning, and other Capital One teams to support the development and integration of semantic technology into Capital One products and services.
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Leverage advanced machine learning techniques, including deep learning and reinforcement learning, to improve fraud detection and prevention models while adhering to privacy regulations. Solid understanding of machine learning algorithms, basic probability, and statistics.
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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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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$248,400 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Validating and training AI machine learning models with annotated training sets in tuning accuracy of the AI models for CLM use cases;Demonstrating knowledge of machine learning and artificial intelligence workloads and considerations on Azure;Demonstrating knowledge of Azure Blob storage, Azure Service Bus and Azure Key Vault cryptography;Designing solutions for custom applications using the Microsoft.
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Booz Allen's Digital Battlespace Team is seeking an experienced full-stack machine learning engineer to build innovative new applications and products in the defense market. 5+ years of experience in software development and machine learning delivering high quality, scalable, and maintainable solutions.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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HQ-ed in McLean, VA and with a presence in New York, London, and Singapore, Pixalate is experiencing remarkable growth and looking to bring a Machine Learning Engineer onboard. As a Machine Learning Engineer, you will be responsible for designing and implementing Generative AI systems (LLMs/NLPs.
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