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Experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, natural language processing or other ML discipline.
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Relevant experience in multimodal data, to include: speech, image, video or text processing and/or data science, applied machine learning or artificial intelligence across the disciplines of Human Language Technology (HLT), Computer Vision (CV), Natural Language Processing (NLP) and Natural Language Understanding (NLU.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
$122,200 - $220,900 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, establishing measures of performance, and human data collection in laboratory and field environments.
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Use analytic methods and advanced knowledge in machine learning, statistics, text mining, natural language processing, computational semantics, computer vision, and data science to develop creative solutions to complex real-world problems.
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We are interested in a variety of topics including data visualization and interactivity, applied machine learning and AI, AI bias and trust, big graphs, natural language processing, data mining, big data management, and heterogenous data analytics.
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As Data Scientist Lead - Risk Data and Analytics, you will be responsible for developing AI models using machine learning, deep learning, and natural language processing, particularly transformer models and Generative AI. Your expertise will be instrumental in developing and implementing predictive modeling solutions for the risk and compliance organization, enabling them to proactively identify and mitigate risks.
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Must have a strong background in one or more of the following: Mathematical, Statistics, Probability, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, Recommendation Systems, Pattern Recognition, Large Scale Data Mining or Artificial Intelligence.
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You should have experience using deep learning, natural language processing, or machine learning systems. Everyday projects range from deep learning, research & development, algorithm development, natural language processing to DevOps. We want to provide access to the right tools and inspiration so you can solve complex problems creatively.
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Design, develop, and implement machine learning models and algorithms to solve complex problems across various domains, including but not limited to recommendation systems, natural language processing, and predictive analytics.
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This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Ph. D. is preferred) At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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Master's degree in Electrical Engineering, Computer Engineering, or related fields with courses work in Digital Signal Processing, Image Processing, Computer Vision, Data Structures, Pattern Recognition, Machine Learning.
$126,984 - $130,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Additionally, applicants with experience in visualization, data analysis, machine learning model research, development, and evaluation, data engineering, multilingual and multimodal modeling, automatic speech recognition (ASR) or language modeling, large language models (LLM) or related topics are especially encouraged to apply.
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Responsibilities NSA Research Scientists are actively expanding the boundaries of what can be accomplished with artificial intelligence, machine learning, human-machine teaming, software reverse engineering, data science, novel architectures, cyber security, high performance computing, and computational linguistics.
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machine learning natural language processing engineer data jobs Company: Veradigm
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