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Build production-ready models using statistical modeling, mathematical modeling, econometric modeling, machine learning algorithms, network modeling, social network modeling, natural language processing, or genetic algorithms.
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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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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
$132,000 - $264,000 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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ML Ops: Design and Build customer data science workloads and apply the best MLOps to productionize these workloads across a variety of domainsTechnical Expertise: Serve as the subject matter expert on AI technologies, including machine learning, natural language processing, computer vision, and other relevant domains.
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Draw on experience with Github, machine learning, advanced programming in SQL and Python, Cloud computing such as AWS, Google and Azure, Tableau, and Simio to design, develop and implement a broad array of business analytics that solve complex problems in a computationally efficient manner by leveraging advanced understanding of statistics and data science.
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As a Quantum Computing Research Scientist Vice President within the Global Technology Applied Research (GTAR) center at JPMorgan Chase & Co., you will have the opportunity to advance the theoretical understanding of quantum algorithms for optimization, stochastic modelling, numerical analysis, machine learning and financial use cases.
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Machine Learning Scientist – Quant AI - Vice PresidentThe Machine Learning Center of Excellence invites the successful candidate to apply sophisticated machine learning methods to a wide variety of complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems.
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Background in Artificial Intelligence (AI), Machine Learning (ML) Natural Language Processing (NLP) Sitting at the intersection of quantitative and investment analysis, the professional will be a "hands-on" player/coach building a team of Data Scientists focused on the implementation of Data Science technologies, techniques and methodologies leveraging Artificial Intelligence (AI) and Machine Learning, advanced analytics, and statistical methods.
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Bachelors or Master's degree in Data Analytics, machine learning, Computer science, artificial intelligence, statistics, data science or related discipline. Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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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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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
$278,100 a yearExpandUpdated 26 days ago - UpvoteDownvoteShare Job
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Experience using natural language processing (NLP), including large language models (LLMs), to extract insights from text data. utilize natural language processing (NLP) and large language models (LLMs) to extract insights and features from text.
$72,100 - $175,100Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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MS or PhD in Computer Science, Statistics, Machine learning or related field, or equivalent experience. Contribute to cutting-edge research in machine learning, including algorithm and method development, specifically applicable to drug discovery and large language models (LLMs.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
$150Full-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Reporting to the Dean of Science, Technology, Engineering and Mathematics (STEM), the Instructor will work collaboratively with administrators, faculty, and staff to advance academic excellence through the use of innovative instructional technology and achieve the appropriate balance between in-person and online learning.
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