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The solutions developed draw on IT-RI’s strong capabilities in statistical modeling, machine learning, natural language processing, information retrieval, statistical genomics, data mining, and big data management and analytics.
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About the RoleAs a Machine Learning Engineer - Technical Lead II for Crowe Intelligent Document Analyzer (CIDA), you will design the future of this document extraction product as it transitions from a combination of Natural Language Processing and embeddings models to fully integrate with Crowe’s in-house Generative AI platform and to leverage Large Language Models (LLMs.
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Good foundation in Machine Learning (ML), Deep Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Hands-on experience in applying Natural Language Processing (NLP) solutions is a plus.
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Natural Language Processing (NLP). You enjoy machine learning and understand supporting these solutions in a production environment using tools like Docker and Git; you’re familiar with Kubernetes.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP.
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Build well-designed, well-engineered, stable, performant mobile applications using Flutter, Kotlin, and/or Java. Guide and mentor other team members by providing oversight and direction. Preferred Qualifications Knowledge of cross-platform development frameworks, such as Flutter/Dart. Understanding of modern SRE best practices.
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Experience developing applications using Flutter. Strong experience using Kotlin and Java in building Android consumer-facing applications. Education Bachelor's degree in Computer Science, Engineering, Information Systems, or related field/work experience.
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Software, Technology, Artificial Intelligence, Robotics, Machine Learning, Data Analytics, Education, Computer Software, Information Technology and Services, Natural Language Processing.
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Our projects include machine learning-powered products, cloud computing infrastructure and strategy, open source stewardship, natural language processing, and more. Quant analytics libraries for users of BQuant and the rest of our team who are creating specific workflow solutions on top such as natural language processing (NLP), backtesting, trading systems integration etc.
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Job Overview “We Power the Magic” That’s our motto at Disney Experiences Technology & Digital. Experience working in an Agile Team consisting of product managers, project managers, design, QA, and tech.
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Analyze user stories, provide realistic estimations, and participate in sprint planning, scrums, demos, and retrospectives. Contribute to the entire development cycle, including technical design, development, testing, experimentation, analysis, and product launch.
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Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation.
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We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
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Helps team advance on plans for use of artificial intelligence, including Natural Language Processing, ChatGPT, predictive analytics, and leveraging machine learning to find hidden insights in data.
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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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machine learning natural language processing hands on jobs Company: American Express
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