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Responsibilities: Developing and training machine learning models using Natural Language Processing (NLP) techniques. Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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As 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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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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Artificial intelligence and predictive analytics in health (i.e. Machine Learning, Large Language Models, Natural Language Processing ) DBMI has research and/or service programs in the following areas: Clinical informatics, clinical research informatics, biomedical data modeling and ontologies, biomedical natural language processing and information retrieval, medical artificial intelligence, privacy technology, global health informatics, equity in informatics, and translational bioinformatics.
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This may also include patent work related to image processing, databases, access management, natural language processing/understanding (NLP/NLU), and autonomous machines/vehicles.
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Ideal candidate would have at least 3 years of industry experience in the field of Artificial Intelligence, Machine Learning, and/or Cloud Computing. We value our client relationships and are committed to learning and furthering the business, as well as legal goals, of each company we work with.
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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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Two years applied machine learning experience in a professional setting, familiar with at least one mainstream deep learning framework, such as TensorFlow or PyTorch. The Senior machine Learning Engineer will be working on different aspects of recommendation and user growth new initiatives, and the product will greatly impact Weee.
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Preferred Qualifications Knowledge of cross-platform development frameworks, such as Flutter/Dart. Knowledge of Typescript Understanding of modern SRE best practices. 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.
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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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Experience with statistical methodologies and machine learning techniques such as: neural networks, graphical models, ensemble methods, forecasting, linear programming, natural language processing, LLMs.
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Join the Anheuser-Busch NAZ Tech Data and Analytics Team as a Machine Learning Engineer. Leverage data science frameworks like TensorFlow, PyTorch, and Spark ML to build robust and scalable machine learning solutions.
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As a Machine Learning Engineer at TRM Labs, you will collaborate with an experienced team of engineers, data scientists, and research scientists to build scalable systems to detect, prevent, and mitigate cryptocurrency fraud and financial crime.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Data Science : Apply natural language processing and machine learning/AI advanced techniques to train and optimize models for automating analysis, processes and insight. Programming experience with implementation of machine learning models on textual data and structured datasets Experience with working on data visualization technologies - Kibana, Bokeh, Leaflet/Folium, Tableau, Splunk, etc.
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machine learning language processing jobs Title: specialist Company: Deloitte
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