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Proficient in Microsoft Azure Storage Explorer, Azure DevOps, Azure Data Factory, Azure Databricks, Azure Data Lake Gen 2, Azure DevOps, Unity Catalog and Git.
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Lead experiments and drive maturity in applying emerging technology disciplines including robotic process automation, machine learning, GenAI, self-serve analytics to the Enterprise Risk portfolio.
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Experience with one or more technologies, such as R Shiny, Databricks, AWS, Azure. Design, build, and deploy data engineering pipelines that extracts, transforms raw data into analytics base tables to support downstream machine learning models using languages such as Python, R and SQL.
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Experience with natural language processing (NLP), computer vision, reinforcement learning, or other specialized areas of AI. Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization Engine technologies (e.g., Docker, Kubernetes.
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Mandatory Skillset: Azure Databricks, ADF, Architecture, PySpark, Azure Architect. Azure Data Architect-Remote. This is Azure Data Architect not Cloud Architect. Experience in creating Data warehouse, data lakes for Reporting, Al and Machine Learning.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) 3+ years of experience with AWS, GCP, Microsoft Azure, or another cloud service.
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Experience with developing enterprise cloud-native solutions, including Kubernetes, Docker, Jenkins and AWS, provisioning computer networking and storage, and setting up servers that the platform is on, including virtual machine (VMs) or networks.
$193,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Utilize JIRA/Azure DevOps for managing work, test cases and testing execution. Somatus, the leader in value-based kidney care, has an immediate opening for a Data Engineer QA to create impact among Somatus’ clients and leadership by developing and testing and maintaining ETL solutions to drive clinical operations, advanced analytics, and machine learning models.
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AI/ML related capabilities such as Aure ML, AWS Sage Maker, Azure OpenAI, AWS Bedrock, etc. 2+ years’ experience working with cloud providers such as AWS and Azure, esp. 2+ years’ experience working with big-data technologies/databases, e.g. Spark, Mongodb, Elastic search, Snowflake, Neo4j, etc.
$260,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Validating and training AI machine learning models with annotated training sets in tuning accuracy of the AI models for CLM use cases;Demonstrating knowledge of machine learning and artificial intelligence workloads and considerations on Azure;Demonstrating knowledge of Azure Blob storage, Azure Service Bus and Azure Key Vault cryptography;Designing solutions for custom applications using the Microsoft.
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Technical Proficiency: Expertise in Python, machine learning tools (Hadoop, TensorFlow, Apache Spark), and deep learning frameworks. Cloud Computing: Proficient in cloud platforms like AWS, Azure, Databricks, and GCP. Agile Work Environment: Ability to work effectively within an agile team setting.
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Central to Data Production is the HIPE application ( Human-in-the-Loop Processing Engine ), which uses sophisticated machine learning and carefully-designed UI/UX to help experts quickly and accurately extract data from medical records as we receive them.
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Part of MITRE Labs’ Infrastructure and Networking Innovation Center, we research, develop, and employ advanced technologies in the areas of network modeling and simulation, dynamic network analysis, machine learning, cellular networking, software defined networking, programmable data plane, operational technology systems, future network science, and more.
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In-depth knowledge of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other AI technologies. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.
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Our technical expertise and innovations are comprised of codeless automation, identity intelligence, immersive technology, artificial intelligence/machine learning (AI/ML), virtualization, and digital transformation.
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