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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.
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Experience using cloud computing for machine learning and deep-learning frameworks such as TensorFlow, PyTorch, Keras. A strong knowledge of NLP and/or computer vision with experience in deep learning (Transformers, RNNs, LSTM, CNN etc.
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Experience with Deep Learning Models (e.g. RNN/LSTM, CNN, VAE, GAN, etc.) Experience solving problems using Machine Learning with Tensorflow or equivalent tools. Our team is made up of robotics specialists from some of the leading technology companies of our time - with deep expertise in artificial intelligence, machine learning, and real-world deployment of advanced technology.
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Good understanding of Machine Learning Algorithms & Deep Learning Algorithms. Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas in Jupytor Notebook.
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Expertise in a variety of Deep Learning architectures and models including Residual Networks, RNN/CNN, Transformer, and/or Transfer Learning in a production environment. Machine Learning Engineer.
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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.
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Experience in Deep Learning techniques, e.g. Transformers, LLM, VLM, vision transformers, transfer learning, LORA, PEFT, CNN, or NLP. Join a highly motivated hybrid-remote team tackling diverse AI projects ranging from traditional machine learning to cutting-edge imagery and LLM. Take ownership over your work, embrace continuous learning, and above all, find joy in what you do.
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Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training. Strong working knowledge of deep learning, machine learning and statistics.
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Proficiency in programming languages such as Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) Familiarity with deep learning techniques and architectures, such as CNN, RNN, and transformers.
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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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Knowledge of a variety of deep learning techniques (regression, classification, CNN, RNN, LSTM, etc) - Must. Knowledge of a variety of machine learning techniques (exploratory data analysis, supervised/unsupervised machine learning, regression, random forest, svm, boosting, cross validation, etc) - Must.
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Experience working with NLP based algorithms such as BERT, ALBERT and deep learning algorithms such as CNN, RNN, RBM, AutoEncoders, etc. Experience working with machine learning algorithms such as Scikit-Learn, TensorFlow, PyTorch, MXNet, etc.
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Experience in designing, testing and deploying machine learning frameworks to rapidly iterate on model development & deployment. And you don t need a finance background to succeed at Fidelity—we offer a range of opportunities for learning so you can build the career you ve always imagined.
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Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in Springfield, VA or St. Louis, MO.
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