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Machine Learning Engineering - Dallas, TX (Hybrid) Experience with one or two of the following: MLOps, Deep Learning methods, NLP, computer vision, sentiment analysis, topic modeling and graph theory, and databases.
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Currently pursuing an MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field. As a Machine Learning Engineer Co-Op, you will work closely with cross-functional teams, including Data Science, Software Engineering, and Product Management, to develop machine learning models, implement solutions, and ensure the successful deployment and maintenance of these models in production.
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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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The faculty members are excellent educators with practical and research expertise in machine learning, data science, artificial intelligence, information security, mobile networking, social networks, bioinformatics, etc.
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Bachelor’s Degree required from an accredited, not for profit university or college, with degree preferably in Computer Science, Data Science, Statistics, Machine Learning, or Mathematics.
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The Mathematics and Computer Science Division at Argonne National Laboratory seeks self-motivated and independent Postdoctoral researcher to develop and apply state-of-the-art probabilistic machine learning techniques for the development of efficient and robust surrogate models for scientific machine learning applications.
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Data science, machine learning, optimization models, Master's degree 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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Demonstrate technical knowledge with a focus on machine learning and geospatial analytics applied to wildfire and/or power systems research challenges. Experience with machine learning and/or geospatial analytics applied to wildfire and/or power systems challenges.
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Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree. 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.
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Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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Lead and participate in solutioning sessions, working hand-in-hand with businesses/clients, translating business objectives into actionable machine learning/data science use casesWhat You'll Bring.
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Educational Requirements:Bachelor's Degree in computer science, machine learning, applied mathematics, econometrics, statistics, engineering, physics, or related discipline required.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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PhD in Computer Science or related fields with a focus on data management, big data, or Machine Learning with AI for science focus strongly preferred. Artificial Intelligence Technologies, Cross Domain Knowledge, Data Engineering, Data Science, Design Thinking, Development Fundamentals, Full Stack Development, IT Performance, Machine Learning Operations, Scalability Testing, Security-First Mindset.
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machine learning computer science jobs Title: engineering Company: Microsoft in Anoka, Minnesota
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