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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Building machine learning models and systems, interpret their output, and communicate their results to internal/client teams and how those outcomes realize business value.
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This a division level analyst position, developing and conducting historian user training, training operators in plant optimization, developing and training operators on the use of trends and dashboards, and developing new applications including iOT, machine learning and artificial intelligence applications.
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Detailed understanding of the Cloud Infrastructure for building & maintaining large data enterprise in cloud platforms like GCP (BigQuery, BigTable, DataFlow, DataProc, DataPrep, Pub/Sub, Machine Learning.
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On top of PLC systems and SCADA, we use the latest technologies including Machine Learning, AI, and Data Analytics to uncover new efficiencies to reduce costs and energy consumption for our clients.
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Data analysis, advanced analytics, data science, machine learning, artificial intelligence, or optimization project experience Solving ambiguous and complex problems through a systems thinking approach.
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Apply machine learning, econometrics/statistics, predictive modeling, return-on-investment analysis, simulation, and data visualization methods to support the development of health policy.
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The ideal candidate will have a solid background in NLP, deep learning, and machine learning, with expertise in fine-tuning LLMs to solve complex language understanding and generation tasks.
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Lead data migration, modernization projects of databases/data warehouses (Oracle or Teradata) from on-premises to AWS/GCP cloud. Define architecture/blueprints, and advise clients on technology strategy, Migration/modernization, cloud adoption.
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Strong background in platforms and tools such as OpenAI, Azure Semantic Kernel, AWS Bedrock, and other machine learning technologies, with a focus on Generative AI and open-source AI frameworks.
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Technical Acumen:Perform model training and validation using various types of machine learning techniques on structured/unstructured data, including imagery, text and graphs. Technical Oversight:Provide technical guidance on model training and validation using various machine learning techniques on structured/unstructured data, including imagery, text, and graphs.
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Job Description: Lead a highly motivated hybrid-remote team tackling diverse AI projects ranging from traditional machine learning to cutting-edge imagery and LLM. Take ownership over your work, embrace continuous learning, and above all, find joy in what you do.
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Data mining, machine learning, statistical modeling tools and underlying algorithms. As a Data Science Sr. Manager at CarMax, you’ll apply your passion and expertise in data, machine learning, and entrepreneurship to create data-science applications that enrich CarMax’s culture of innovation.
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Strong foundational knowledge of machine learning (ML) algorithms, natural language processing (NLP) and AI Model Evaluation. Hands on experience with big data frameworks and modern data technologies (Snowflake, dbt, Airflow, Tableau, SQL.
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Developing and deploying machine learning pipelines using Vertex AI and Kubeflow for data processing, feature engineering, model training, evaluation at scale in production on GCP ensuring data quality, integrity, and security.
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Net, C#, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Python, Data Modeling, SQL, SSIS, SSAS, SSRS, Power Automate, Power Platform, AI Builder, Power Apps, Blue Prism, Automation Anywhere, UiPath Studio, Orchestrator, ERP, QuickBooks, SAP, NetSuite, Oracle, API, JSON, XML, Web Services, SOAP, Postman, Fiddler, Integration, Custom Activities, DLL, Insight, Automation Hub, Task Capture.
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machine learning on jobs in Dallas, WI, Canada
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