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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 Today - 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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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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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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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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Code, working with hardware and software, ability to grasp high order concepts in physics, microscopy, hardware design, automation, and robotics, experience with computer vision and machine learning, experience with image processing, experience working with an agile team, experience in SQL.
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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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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch.
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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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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.
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Experience in Development and/or validating probabilistic models, Bayesian models, Decision Trees, Random Forest, Ensemble Models, Neural Networks, PCA/Preventive Crime Research, Logistic / Linear Regression, Linear / Non-Linear Optimization, Support Vector Machines, Natural Language Processing, Large language models, Graphic deep learning, audio programming.
$100,000 - $142,250Full-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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