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Knowledge of deep learning architectures and techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and Generative Adversarial Networks (GANs.
$105,000 - $145,000 a yearExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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You will be impacting every aspect of the business and it will require various techniques, from diving deep into data with SQL and Big Data tools, all the way to deploying modern machine learning models.
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Build, validate, test, and deploy machine learning or other data science models to predict and influence the behavior of consumers with the goal of optimizing products & processes.
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As a Technical Product Manager CW on the Recommendations Data Augmentation team, you will leverage your unique balance of business, product, and deep technical skills to drive development and improvement of datasets and machine learning models to support the online recommendations space.
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Extensive experience in machine learning model design, data pipeline design, experimentation and validation design, system design, and/or architecture design. Extensive background of deep learning architectures and techniques, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM), and Generative Adversarial Networks (GANs.
$180,000 - $225,000 a yearExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Advanced degree (MSc/PhD) in Computer Science, Economics, Engineering, Operations Research, Physics or Mathematics/Statistics preferred. Experience combining user research and data science methodologies across multiple products and teams.
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We are looking for hardworking Solution Architect Managers to join the NVIDIA AI Enterprise (NVAIE) SA Segment Team, which focuses on Machine Learning, Deep Learning, Accelerated Data Analytics, and Cloud.
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Experience with deep learning framework and infrastructure like TensorFlow or PyTorch. Develop data science solutions based on tools and cloud computing infrastructure. Bachelors degree in computer science, mathematics, physics, statistics, or related field.
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Physics, Computer Science, Mathematics, Chemical Engineering, Materials Science, Mechanical Engineering, Electrical Engineering, Data Science. Experience in image processing and data analytics, with deep learning/hybrid algorithms is preferred.
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You will also be implementing methods in cloud environments to a blend of data science skills (remote sensing, physics, geospatial, imagery process, etc) and computer science understanding is a plus for this position.
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What You Need for This Position Current knowledge of deep learning concepts (e.g. transformer models, data parallelism, model parallelism). We fuse data strategy with data science and design driven innovation to create customer technologies for commercial and federal customers.
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The specific project will be related to developing machine learning algorithms for cancer diagnosis and response modeling using molecular and imaging data (pan-omics) with new deep, generative AI, and reinforcement learning approaches.
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Prepare the data for the growth of predictive and advanced analytical capabilities which include machine learning, artificial intelligence, and deep learning. Bachelor’s and/or Master’s Degree in Mathematics, Physics, Engineering, Computer Science, Data Science, Statistics with a business or economics focus.
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Ph. D. in Computational Physics, Applied Physics, Applied Mathematics, Computer Science, Biological Science (e.g. Cell Biology, Biophysics, Bioengineering), or related science or engineering field; OR equivalent combination of degree and experience.
$82,650 - $115,700 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Have 4+ years of experience in designing and implementing algorithms involving one or more of the following: classification, clustering, deep learning, decision making, AI explainability, stochastic processes, detection and estimation theory, information theory, Bayesian inference of time varying systems, tracking and data fusion (e.g., KF, MHT, IMM, etc.
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