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Good understanding of machine learning, deep learning (including LLMs) and natural language processing and ability to optimize machine learning models to adapt to solving various kinds of issues.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
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Develop, implement, and optimize cutting-edge machine learning algorithms related to image processing, signal processing, RADAR, and Synthetic Aperture Radar (SAR). Minimum 5 years of experience in a similar role, with a focus on machine learning, image processing, signal processing, RADAR, and Synthetic Aperture Radar (SAR.
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They are seeking a highly skilled Bioinformatician with extensive experience in Large Language Models (LLMs) and Natural Language Processing (NLP) to join their cutting-edge team.
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In this specific position, the analyst will focus on models built in house and by third parties with machine learning and AI technologies primarily for the purpose of Natural Language Processing (NLP) and/or Generative AI.
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In-depth knowledge of Natural Language Processing concepts including transformer architecture and other generative AI technologies Strong computing and programming background and knowledge of one or more languages such as Python and Java Experience with ML/AI computing platforms and tools such as PyTorch, TensorFlow and Keras Experience with GPU programming, multi-core, or distributed programming.
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3+ years of experience in the fields of Natural Language Processing, Dialog Systems, Contextual Understanding, Machine Learning, Deep Learning, Computer Vision.
$190,000 a yearFull-timeExpandApply NowActive JobUpdated 19 days ago - UpvoteDownvoteShare Job
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Serving as a subject matter expert regarding the latest industry knowledge to improve the organization's systems and/or processes related to Machine Learning, Deep Learning, Responsible AI, Gen AI, Natural Language Processing, Computer Vision and other AI practices.
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Deep understanding and experience with advanced analytics, Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) or Computer Vision (at least 3 of these areas.
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We are a growing subsidiary of a large public company that is hiring a talented Lead ML Engineer / Senior Machine Learning Engineer! 100% REMOTE Senior ML Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Use techniques such as deep learning, natural language processing (NLP), and reinforcement learning to tackle problems in protein structure prediction, gene expression, and drug-target interactions.
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Expertise with Google Cloud Platform’s distributed Machine Learning, Data Science and Data Engineering tools (e.g. BigQuery ML, VertexAI, AutoML, Docker, Kubernetes, Kubeflow, Dataproc) As a Sr. Data Scientist, reporting into the Head of Data & Strategy at TRKKN North America (NA), you’ll focus on building scalable machine learning and AI products to help evaluate and optimize the business impact of our clients’ marketing investment.
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Act as Data Science Subject Matter Expert (SME) in the delivery and development of machine learning and AI products. Being on the bleeding edge of marketing technology and innovation means you will have an unparalleled opportunity for learning, along with personal and professional growth: there's never a dull moment here.
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As a Senior Associate in the role of Machine Learning Scientist specializing in Natural Language Processing (NLP), you will be tasked with the application of advanced machine learning techniques to intricate tasks such as natural language processing, speech analytics, time series, reinforcement learning, and recommendation systems.
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