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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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Experience with training deep learning models for computer vision or natural language using frameworks, including TensorFlow, PyTorch, or Keras. participate in partnerships with data science leaders, like our partnership with NVIDIA to deliver Deep Learning Institute (DLI) training to the federal government.
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Experience using existing AI framework (e.g., TensorFlow, Caffe, MXNet, Cognitive Toolkit, Torch) Apply a variety of data science techniques to tackle customer challenges to include machine learning, generative AI, natural language processing, computer vision, reinforcement learning, statistical modeling, mathematical optimization, and data visualization.
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Technical Proficiency: Expertise in Python, machine learning tools (Hadoop, TensorFlow, Apache Spark), and deep learning frameworks. Technical Proficiency: Expertise in Python, machine learning tools (Hadoop, TensorFlow, Apache Spark), and deep learning frameworks.
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Expertise in common Geospatial software applications and tools, such as visual programming (JEMA, FADE/MIST, ECO/ETAS), Python, SQL, Git, GIMS, AWS Sagemaker, AWS Cloud, ESRI ArcGIS, statistics (descriptive, Bayesian), Markov-Chain modelling, TensorFlow, Linear Algebra, R, SAS, NLP.
$140,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP. At least four years of experience developing scalable, production-ready NLP solutions using sci-kit learn, Keras, TensorFlow, PyTorch, Spark NLP.
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Experience with deep learning frameworks such as TensorFlow, PyTorch, etc. We provide cutting-edge SaaS technology solutions, data, and research to identify, quantity, and mitigate ad fraud and data privacy compliance risks in digital advertising.
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4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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Machine Learning Frameworks: Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Big Data Technologies: Experience with big data technologies like Apache Spark or Apache Kafka.
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Leverage deep learning frameworks (e.g., PyTorch, Tensorflow) to develop deep learning solutions, tailoring them to the application area. The Machine Learning/Data Science Research Engineer will participate in an end-to-end design and implementation of deep learning solutions for application in network/graph representation learning (NRL) and graph construction/generation/completion.
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Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Preferred skills: NLP, Text mining, Tableau, PowerBI, SAS, Tensorflow. Spring boot, Microservices, Docker, Jenkins and REST API's experience.
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Experience with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Design and implement scalable AI/ML models for tasks such as information retrieval, natural language processing, predictive analytics, and automation.
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Strong proficiency in programming languages like Python, R, or SQL.Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Currently, ManTech is seeking a motivated, career and customer-oriented Data Engineer to join our team in Fairfax, VA, Warrenton, VA , The Pentagon or Fort Washington, MD. We are seeking a passionate and skilled Junior Data Scientist to join our growing team.
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Experience in TensorFlow and/or PyTorch. The Machine Learning Engineer will work across multiple research areas developing and maintaining custom applications and data pipelines featuring generative AI, natural language processing, LLMs, and other foundation models.
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Duties:Building Machine Learning Models and Systems: You will work with machine learning frameworks such as TensorFlow, PyTorch, Torch, and Caffe and modern programming languages including Python, C/C.
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