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Experience with Artificial Intelligence/Machine Learning (AI/ML) applications for image processing. Develop image processing algorithms for Electro-Optical/Infrared (EO/IR) or Hyperspectral Imagery (HSI) data.
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Design and implement distributed data processing pipelines using Spark, Hive, Python, Airflow, and other tools and languages prevalent in the Hadoop ecosystem. As a Sr. Big Data Engineer, you will work with a variety of talented teammates and be a driving force in technical initiatives that will accelerate analytics at Client.
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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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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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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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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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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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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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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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Experience with machine learning methods in Recommendation System, Search, Causal Inference, Optimization, Time Series, Natural Language Processing, Large Language Model, Computer Vision.
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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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Expertise in the physics of additive manufacturing processes such as wire arc DED and laser powder DEDExpertise in physics-based simulation and its integration with machine learning models.
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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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Working understanding of enforcement of compliancy requirements and being able to supply audit data. Lead a geographically dispersed team of ~ 20 consisting of DevOps Engineer, Value Stream Delivery CI/CD, Deployment, DevSecOps, SRE and Observability.
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