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Experience with Artificial Intelligence/Machine Learning (AI/ML) applications for image processing. Develop novel algorithms, models, and data processing schemes forElectro-Optical/Infrared (EO/IR) or Hyperspectral Imagery (HSI) data.
$135,150 - $241,250 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Develop image processing algorithms for Electro-Optical/Infrared (EO/IR) or Hyperspectral Imagery (HSI) data. Experience performing geolocation or state estimation from space-based imagery data and associated spacecraft metadata.
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Data Scientists contribute to projects involving one or more of the following disciplines: Data Science, Applied or Theoretical Machine Learning, Deep Learning, Deep Reinforcement Learning, Physics Inspired ML, Classification Systems, Natural Language Processing, Artificial Intelligence, or Computer Vision.
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Mentor team members and stay current with the latest research to advance organizational knowledge in computer graphics, machine learning and related technologies. Drive the ideation and development of innovative solutions, leveraging your deep understanding of 3D graphics and machine learning.
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KARL STORZ is currently seeking a highly motivated Data Analyst to join the Operations team. This opportunity will get you working on large-scale structured, unstructured data sets, and apply various data engineering and modeling techniques on real-world datasets to build and deploy models.
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Education and Experience: Bachelor’s degree from an accredited college or university in a related field and six years of relevant experience; or two years in a MWD Associate Environmental Specialist classification; or Master’s degree from an accredited college or university in a related field and four years of relevant experience.
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In collaboration with campus partners such as the General Counsel and the Associate Dean of Faculty Affairs, provide guidance to search committees in adhering to institutional policies and legal requirements throughout the search process, while also outlining standard search timelines and processes to maintain consistency and efficiency in recruitment.
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Strong knowledge of enterprise applications (i.e., PLM, ERP, MES) and data analysis applications/tools (i.e., MS Excel, SQL, Tableau). Strong knowledge of enterprise applications (i.e., PLM, ERP, MES) and data analysis applications/tools (i.e., MS Excel, SQL, Tableau.
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Manage services from Public Cloud Hyperscalers like Microsoft Azure, Amazon AWS, Oracle OCI, Google GCP, and Alibaba Cloud on services like Cloud Compute, Storage Services, Data Services, DevOps, CI/CD, MicroServices, Service Mesh, Containerization, Artificial Intelligence, Machine Learning platforms and End-to-End Observability.
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Experience with machine learning methods in Recommendation System, Search, Causal Inference, Optimization, Time Series, Natural Language Processing, Large Language Model, Computer Vision.
$140,100 - $210,100 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deploying machine learning algorithms, working with data developers and solution architects to establish the entire project life cycle in an Azure cloud environment. 6 years An equivalent of six or more years of experience applying advanced statistical concepts, machine learning techniques, forecasting and other methods to solve complex problems using structured and unstructured data.
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Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.
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Pay Range is: $18.00 - $34.75 Hourly Return to Job Search Facility Maintenance Technician If you are highly motivated and enjoy collaborating with others, consider joining U-Haul as a Facility Maintenance Technician.
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You will develop robust and scalable data pipelines, ML model hosting, and backend services for enterprise line of business applications in Python, VertexAI, Airflow, dbt, Flask, PostgreSQL, BigQuery, Docker, Kubernetes, and more.
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Continuously improve knowledge and abilities in the areas of software and data engineering, statistical learning, and machine learning. Implement new statistical, or machine learning, models and maintain existing models, used in all facets of player acquisition and game play.
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