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Familiar with commonly used machine learning and deep learning algorithms, understand basic network model structure (DNN/LSTM/CNN, etc.) 3+ working experience in one of the following fields: machine learning, NLP(Natural Language Processing), multimodal, and computer vision.
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Use Deep Learning models like CNN, RNN and NLP (BERT) for solving various business use cases like name entity resolution, forecasting and anomaly detection. Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization.
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Masters with at least - years of experience; Strong software engineering practices in Python with machine learning development experience towards a product not just academical settings Strong Machine Learning background with deep understanding of different types of machine learning algorithms (, CNN, RNN, LSTM, Transformer, and Reinforcement Learning.
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Proficient in Python language, familiar with typical deep learning frameworks (TensorFlow/PyTorch) and models such as CNN, Transformer, GBDT, LR, etc. FedML's researchers and software engineers and product teams are busy developing the next-generation FedML platform for machine learning and artificial intelligence and we're looking to grow our team with skilled professionals who bring fresh ideas from all areas, including machine learning and its applications, computer vision, natural language processing, large-scale system design, distributed/cloud computing/systems, MLOps, security/privacy, mobile/IoT systems, and networking.
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Working knowledge across the following areas with experience in at least one: - interfaces, optical, sensors, modules, ISP and algorithm fundamentals, CV/ML - network impacts on latency, throughput and Jitter, VoIP, video communications - general Machine learning (DNN, CNN, RNN.
$167,000 - $230,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Publications in top machine learning conferences/journals such as JMLR, ICLR, NeurIPS, ICML, ACL, CVPR. -Knowledge in Algorithms, Optimization, Probability, Statistics and Information Theory Working experience in one or more of the following research directions in Neural Networks: Deep Reinforcement Learning, Federated Learning, Transformer, Transfer Learning, Online Learning, Generative Neural Network, Graph Neural Network, CNN, RNN etc.
ExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Experience in Machine Learning and Deep Learning, including regression, classification, neural network, and Natural Language Processing (NLP). Experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems, and generating data visualizations using R, Python.
Full-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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General Machine learning (DNN, CNN, RNN, GenAI LLM) Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
$204,000 - $281,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Strong background in Deep Learning and classical Machine Learning, including but not limited to CNN/RNN architectures, GAN, active learning, k-shot learning and model complexity reduction techniques.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvote
Solutions Prototyper - GenAI, Customer Acceleration Team, CAT - Prototyping And Customer Engineering
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Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer) - Strong working knowledge of deep learning, machine learning and statistics. Are you looking to work at the forefront of Machine Learning and AI.
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Experience in designing and building highly scalable distributed ML models in production (Scala, applied machine learning, proficient in statistical methods, algorithms). We are looking for someone with a strong knowledge of ML, NLP, Deep Learning, Knowledge Graphs and experience working with massive amounts of data.
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Experience in deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc) and familiarity with CNN/LSTM model architectures. Work within and coordinate with a small team to analyze, implement, and optimize DirectML-TensorFlow and PyTorch for machine learning models.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning.
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Some example statistical and machine learning methods we use on the data science team include Regression Analysis, Naive Bayes, Random Forests, PCA/LDA/IDA, and Neural Networks and related architectures (CNN, RNN, Transformers, LSTMs.
ExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Experience in two or more applicable data science disciplines: statistical modeling, machine learning, data mining, time series data analysis, or data engineering. Hands-on experience in common machine learning algorithms including random forest, logistic regression, PCA, support vector machines, Neural Networks (convolutional/transformers/recurrent/etc), KNN, KMeans, or equivalent.
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