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E.g. Alteryx, PowerBi, Tableau, Snaplogic and RPA technologies (UiPath, Automation Anywhere, PowerAutomate, etc), and machine learning/Artificial Intelligence. Demonstrate knowledge of technologies that support collaboration, automation and data-driven story-telling including: Microsoft Products (Teams, PowerBI, MS Office), G-Suite (Google), and business intelligence tools.
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KEYWORDS Machine Learning | Physics | Embedded Systems | Signal Processing | Data Analysis | Nvidia | Electrical Engineering | Cloud Computing | Cuda | TensorRT | Radio Frequency | Transmission Processing | Linux OS | Pytorch | Python | Edge Computing.
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Machine learning will cover everything from data science, Artificial intelligence, business analytics, deep learning, and computer science. Difference between Machine learning, Artificial Intelligence and Deep learning.
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Advanced data analytics designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, SQL DWH, Stream Analytics, Machine Learning, R Server, Synapse, Azure Machine Learning (AML), Azure Kubernetes Service (AKS) for model deployments, Vector and Retrieval-Augmented Generation (RAG) implementation.
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Understanding of strengths and weaknesses in application of Machine Learning and Artificial intelligence to applications in Transaction monitoring and Sanctions screening. Director, Model Validation for SHUSA Compliance models (Transaction Monitoring, Sanctions Screening, Fraud Risk, etc) will be responsible for leading the independent validation of models used by various Compliance groups in conformance with regulatory guidance on model risk SR- and other regulatory requirements around Compliance models.
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Job DescriptionGen AI Solution Architect/Delivery Lead -DescriptionJob Title: Databricks Generative AI Solution Architect / Delivery LeadJob Location: Hybrid (preferred base cities: Atlanta, NYC, Chicago, NYC, Dallas, Houston, and Seattle)Job description: The AI Architect will leverage expertise in data science, specifically in artificial intelligence, machine learning, and software architecture to address complex business challenges.
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Ideal applicants should have a background on biomedical image analysis, computer vision, pattern recognition and/or machine learning. Work in our group focuses on developing innovative image analysis, machine learning, AI and data science methodologies for multimodality imaging, and also on incorporating such methods into clinically relevant applications.
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What you bring to the table: 3+ years professional experience in technology research in the emerging technology space or a related position (related investment banking, equity research, consulting, or journalism experience), preferably in artificial intelligence, quantum computing, blockchain, AR/VR, or other deeptech areas.
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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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Deep knowledge of ASP.NET Core, MVC, Web API, JavaScript, JQuery, Python, Google Analytics, Azure artificial intelligence platforms, and mobile application development (Xamarin, React Native, and iOS Native.
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Bachelors or Master's degree in Data Analytics, machine learning, Computer science, artificial intelligence, statistics, data science or related discipline. Experience in Data science and Machine learning using Python, R, Java, C#, Spark, AutoML, TensorFlow, Amazon AML, Microsoft machine learning studio, PyTorch, IBM Watson and any graph DB.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Databricks Machine Learning Certificate Preferable. Collaborate with teams to deliver scalable data architecture supporting analytics and business intelligence. The candidate should have hands-on experience with various Azure services including but not limited to Azure Data Factory, Databricks, Data Lake, and Power BI.
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As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. CAS works across our investment teams and client businesses, in partnership with BlackRock's analytics, data and technology teams, to transform data into intelligence, deploy financial models on Aladdin, address client challenges with innovative technology, and deliver solutions across asset classes and client segments.
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Monitor existing and proposed regulations affecting international trade, including artificial intelligence / machine learning and cloud regulations which impact import / export control regulations.
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machine learning artificial intelligence jobs Title: artificial intelligence in New York, Columbia, Missouri
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