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Natural Language Processing (NLP): Apply advanced NLP techniques to understand and interpret user input, including intent recognition, entity extraction, sentiment analysis, and language understanding.
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Minimum of 2 years developing applications using AI, natural language processing (NLP), and/or speech recognition. Experience evaluating and testing NLP systems or LLMsExperience using Bot Framework SDK, Bot Framework Composer or Power Virtual Agents (PVA)Experience with AWS AI Services, Lex, Comprehend, ChatbotExperience with Azure Cognitive Services, Azure AI Services, Azure Bot Service (ABS)Software engineering experience with PythonExperience with CI/CD pipelines like Jenkins or Azure DevOps.
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Strong mathematical background with strong knowledge in at least one of the following fields: statistics, data mining, statistics, operations research, econometrics, and/or information retrieval (image processing (OpenCV) and natural language processing is a plus.
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Machine Learning Integration: Integrate ML algorithms and models into chatbot systems to enhance response generation, question answering, and user engagement. Platform Integration: Collaborate with software engineers and developers and integrate chatbot systems into various platforms, such as websites, mobile apps, messaging applications, voice assistants, or CRM. Ensure seamless integration and compatibility with existing systems and APIs. Collaboration: Work with cross-functional teams to understand business requirements and translate them into technical solutions.
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3+ years of Experience with Apache Spark, Kafka, Pig, Oozie, Flume, and Streaming and similar distributed computing technologies. Minimum of 10 years of experience in enterprise data architecture, including data requirements collection, data architecture analysis, evaluation, documentation, data modeling, design, development, model validation, and data integration.
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API Configuration: Configure APIs for chatbot solutions in the cloud connecting to external systems and various data sources. Documentation and Training: Document chatbot architectures, design decisions, and implementation details.
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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Nave Bayes, Neural Networks, regression, image processing, natural language processing.
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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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Established expertise and genuine passion for natural language processing (NLP), machine learning, deep learning, and large language models. Experience training, fine-tuning and deploying large language models (LLM.
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You will lead a team of researchers creating data-driven algorithms for ATG. The initiatives will include both short-term and long-term research in areas such as artificial intelligence, machine learning & data mining, natural language processing, big data systems, information and data visualization, and social & cognitive science.
$199,300 - $247,500Full-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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B. Python, R, TensorFlow, SciKit-Learn, SPSS), Natural Language Processing oder LLMs. At IBM, we pride ourselves on being an early adopter of artificial intelligence, quantum computing and blockchain.
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Knowledge of implementing and fine tuning of Natural Language Processing (NLP) use cases. Thousands of organizations worldwide, including Barclays, Cisco, eBay, Fairfax, ING, Goldman Sachs, Microsoft, The Mayo Clinic, NASA, The New York Times, Wikipedia, and Verizon, use Elastic to power mission-critical systems.
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The degree programs are interdisciplinary drawing on CU Boulder faculty expertise in statistics, applied mathematics, data science, computer science, information science, geospatial analytics, natural language processing, business analytics and more.
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Experience with data science or building machine learning models is required, specifically natural language processing (NLP). Utilize natural language processing (NLP) to automate data quality check on free text fields for ongoing clinical trials.
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In this role, the primary focus is on recommender systems, so the candidate must be able to leverage machine learning techniques such as collaborative filtering, deep learning, reinforcement learning as well as Natural Language Processing techniques important in dealing with content metadata.
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