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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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In this role, you will collaborate with researchers to develop machine learning methods for computational biology and drive the implementation and testing of novel research ideas using cutting-edge deep learning techniques.
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Ph. D. in Bioengineering, Biochemistry, Biostatistics, Chemical Engineering, Computer Science, or similar discipline, with 0-5 years of experience and a strong focus on deep learning and/or cell engineering.
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Should be competent with at least one numerically focused programming environment such as Python or Matlab using the native linear algebra, image processing, and machine learning libraries.
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You will have demonstrated experience with Python and deep learning libraries such as Pytorch and/or TensorFlow and/or JAX. The Structural and Computational Biology (SCB) group within Prescient Design seeks exceptional researchers who have a demonstrated research background in protein structural biology and design, machine learning, and project management, a passion for research and technical problem-solving, and a proven ability to implement ideas and apply methods.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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With a long-term vision and a strong commitment to the AI field, the Team conducts research in a range of areas including natural language processing (NLP), computer vision (CV), and speech recognition and generation.
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Experience and/or proficiency in Machine Learning, Artificial Intelligence, and/or Natural Language Processing. Experience developing and delivering technology in at least two of the following areas: data analytics, machine learning, data visualization, geospatial analysis, web services, or database development.
$96,000 - $144,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience with natural language processing (NLP) is a plus. Familiarity with deep learning approaches and Large Language Models. The Machine Learning Engineer II reports to the Director of Architecture.
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Required Technical Skills: Deep knowledge of AI principles, including natural language processing (NLP), computer vision, and reinforcement learning. We offer a unique and immersive online learning platform, powering corporate technical training in fields such as Artificial Intelligence, Machine Learning, Data Science, Autonomous Systems, Cloud Computing and more.
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Is required (test required)Algorithmic trading experience is required (essential), whether personal or professional experience Desirable Skills: Prior experience as a Quantitative Trader/ ResearcherExperience with Machine Learning, Natural Language Processing or Deep LearningKnowledge of the DeFi and Web 3.0 ecosystem.
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A demonstrable curiosity about high-frequency trading, quantitative trading, and sound knowledge of cryptocurrency trading. Role DescriptionWe are looking for Quant Traders that have developed a live trading track record and are looking to join a reputable fund to continue managing their own desk with related P&L responsibilities.
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183; Utilize methods in the areas of Artificial Intelligence (AL), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP) to design and implement data solutions.
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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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Leveraging computer vision, natural language processing, machine learning, and vertical-specific large language models (LLMs), Lily AI enhances customer shopping experiences by injecting consumer-centric language throughout the retail technology ecosystem.
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machine learning natural language processing deep jobs Title: director Company: Intuit
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