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Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machine-learning, and deep learning. Demonstrated experience using CUDA and NVIDIA GPU accelerated libraries for AI, machine-learning, and deep learning.
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The AI COE is seeking a Senior Data Scientist with experience in Conversational AI, Generative Large Language Models, Natural Language Processing, Machine learning, various deep learning related technologies, predictive and prescriptive analytics.
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Participate in partnerships with data science leaders, like our partnership with NVIDIA to deliver Deep Learning Institute (DLI) training to the federal government. You’ll develop algorithms, write scripts, build predictive analytics, apply ML and deep learning, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help drive innovation, research, and development for our military and government leaders to make informed decisions.
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Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g., regression, classification, Time Series analysis: e.g., ARIMA, Traditional machine learning methods: e.g., Random Forest, ensemble model techniques, Optimization: e.g. linear programming.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. 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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Programming skills and familiarity with GPU based technologies like CUDA, CuDNN and TensorR and background with deploying machine learning models on data center, cloud, and embedded systems.
$144,000 - $270,250 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Strong knowledge in: Regression, Classification, Machine Vision, Natural Language Processing, Deep Learning and Statistical modeling. Implement machine learning models, including deep learning, reinforcement learning, and other AI techniques, to solve complex business problems.
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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.
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As a Senior Data Scientist for our team, you'll leverage your expertise in machine learning, deep learning and reinforcement learning to create large-scale, personalized recommendation models for our omni-channel retail platform, with a focus on exploring and implementing cutting-edge technologies like Large Language Models (LLM's.
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One of the most commercially successful conversational AI companies in the world, Conversica is building the next generation of our artificial intelligence platform and we are looking for data science interns in the areas of natural language processing, natural language generation, and deep learning.
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Advanced knowledge of math, statistics, multivariate analysis, statistical tests Advanced Python coding skills Experience with one or more machine learning frameworks such as TensorFlow and/or PyTorch Understanding of numerical implementations Understanding of cloud computing Knowledge of data querying knowledge of EMG, EEG, ECG, IMU, CV algorithms Experience with C.
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2+ years of experience in Data Science or a related field, with a focus on building NLP/LLMs or Deep Learning models. Design and implement machine learning algorithms for NLP/LLMs or deep learning models at scale to meet business requirements.
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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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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.
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Querying, algorithms, data engineering, natural language processing, engine recommendation, experimentation, programming, data storytelling and intelligence, predictive modeling, and machine learning.
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