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Bio : The Machine Operator is responsible for operating equipment used in the production of spirits at ASB. Including but not limited to distillation equipment, pumps, bottling lines, filters, material handling, boiler.
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Transform your career to the next level with GDIT as a Solutions Architect where you can elevate your skills in Data Science, Machine Learning, or leading AI techniques and technology expertise into solutions in support of our Government customers.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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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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Background in Machine Learning frameworks such as PyTorch, TensorFlow, SparkML or Keras, Scikit Learn. Experience in Machine Learning related field, preferably Computer Vision. In-depth knowledge of image processing, statistical modeling, advanced mathematics, data integration concepts and tools.
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We seek a qualified Machine Learning Engineer in San Diego, National Capital Region, with remote/telework eligibility. Review, assess, and provide advice in the development of engineering processes for Artificial Intelligence and Machine Learning (AI/ML) programs and projects.
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We are seeking individuals with a profile of skills in psychometrics, statistical computing & programming, simulation-based research, natural language processing, and machine learning. Increasingly, we find ourselves conducting data analyses of rising complexity involving traditional statistical methods alongside techniques related to machine learning.
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Support GDIT’s FedCiv business areas by developing solutions to deliver capabilities, including Data Science and Machine Learning. Familiarity or experience with developing solutions for proposal within any of U.S. Government Agencies, to include but not limited to the following: Department of Transportation (e.g., FAA), NASA (including JPL), Department of Commerce (e.g., NOAA), or Department of Energy (e.g., HQ, NNSA.
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Machine Learning Engineer. As an experienced engineer, you know that machine learning (ML) is critical to understanding and processing massive datasets. Knowledge of Databricks, Tensorflow, Langchain, or Kubernetes.
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Experience with machine learning hardware, including AMD, NVIDIA DGX, or small form factor HW, such as Jetson or Xavier. Experience with wide variety of machine learning programming languages, including Python, TensorFlow, or JavaScript.
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Our mission is to change the world by making people happy with coffee.
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Model Development: Design, build, and train machine learning models, including but not limited to deep learning models, decision trees, and ensemble methods, to solve complex business problems.
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Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities. Familiarity or experience with developing solutions in response to U.S. Government Agencies' solicitations, to include but not limited to the following: Department of Transportation (e.g., FAA), NASA (including JPL), Department of Commerce (e.g., NOAA), Department of Energy (e.g., HQ, NNSA), or National Science Foundation.
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As the Lead Machine Learning engineer, you will be responsible providing technical guidance and mentorship to team members to ensure the development of their skills. As the Lead Machine Learning engineer, you will be responsible providing technical guidance and mentorship to team members to ensure the development of their skills.
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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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Title: machine Company: Candidate Source For in Springfield, VA
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