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Deep Learning, Red Hat OpenShift, Tensorflow. 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.
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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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5-7 years experience across deep learning frameworks like Keras, TensorFlow or PyTorch and machine learning packages (sklearn, etc.) The Senior Machine Learning Engineer will participate in research and development efforts aimed at solving problems in analyzing large-scale clinical data with a mission of improving human health.
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We want Data Science, Machine Learning, Data Analyst, and Java Full Stack candidates. For Data Science/Machine Learning Positions. Machine Learning Engineers.
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Currently, we are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, data analysts, data scientists, and machine learning engineers for full-time positions with clients.
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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer Do you have a passion for invention and self-challenge? Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, 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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Two years applied machine learning experience in a professional setting, familiar with at least one mainstream deep learning framework, such as TensorFlow or PyTorch.
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Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, PyTorch, Tensorflow/Keras, MLlib, etc. 100% REMOTE Senior ML Ops Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company.
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NLP, Text Mining, Tableau, PowerBI, Databricks, TensorFlow. NLP, Text Mining, Tableau, PowerBI, Databricks, TensorFlow. Spring Boot, Microservices, Docker, Jenkins, GitHub, Kubernetes, and REST APIs experience.
$150,000 a yearRemoteExpandApply NowActive JobUpdated 30 days ago - UpvoteDownvoteShare Job
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We work with companies funded by the best investors including Sequoia Capital, Lightspeed Ventures, Tiger Global Management, A16Z, Accel, DFJ, and more. Strong programming skills in Python with extensive experience with the scientific and deep-learning stack (numpy, pandas, numba, torch, tensorflow, jupyter.
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Experience optimizing the model training process for deep learning frameworks such as PyTorch, Tensorflow, Keras or similar. As a Senior Machine Learning Engineer, you will work on a broad set of domains that power a data-driven transformation of our standard business procedures across channels.
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Proficiency in at least one of the following deep learning framework: TensorFlow or PyTorch. Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems and bring it to large-scale real-time recommendation pipeline; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams.
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5+ years of practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python, preferably within the AWS ecosystem. Senior Machine Learning Operations Engineer.
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