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Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning. Senior Software Engineer, US Risk Technology page is loaded. As a Software Engineer on the US Risk Technology team, you'll serve as a technology partner for the US risk management function.
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We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Understanding or hands on experience with Lex, Nuance Mix, Dialog Flow, AWS and Google Cloud, R, Power BI, Tableau, Alteryx.
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Leverage AWS cloud services for data storage, processing, and analytics, optimizing cost and performance with CloudFormation and Jenkins. Proven experience with AWS cloud services for data storage, processing, and analytics.
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The team tackles problems of massive scale, with a critical data footprint that has bottomline business impact, resiliency & availability requiring the best techniques within Big Data Analytics and Machine Learning, all while providing a superior analyst experience on our tools.
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We expect our Machine Learning Engineer to have excellent skills with Python and its machine learning / natural language processing libraries, and have working experience with both structured and unstructured data.
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Machine Learning | AI | TensorFlow | Deep Learning | AWS | PyTorch | Django | MLOps | Computer Vision | Imaging | Python | GIS | Location Data | Aerial Data | As an AI/Machine Learning Engineer, you can expect to earn up to $150,000 (depending on experience) and highly competitive benefits.
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A record of continuous learning and adaptation to stay updated with the latest in machine learning, generative AI, cloud technologies, and data compliance standards.
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ReflexAI brings the best in machine learning and natural language processing to mission-driven, people-centric organizations via innovative tools that transform how they train, develop, and empower their frontline teams.
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Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., public cloud, artificial intelligence, machine learning, mobile, etc.
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Experience with cloud-based systems such as AWS, Azure, or Google Cloud, including expertise in IaC and CaC; Ansible, Terraform. Expertise in cloud containerization; design, develop and troubleshoot.
$120,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Cloud and/or security certifications related to Cloud Architecture, Data Engineering, DevOps Engineering, DevSecOps, and Machine Learning is advantageous. Some experience with cloud-based and on-prem data solutions (Apache Hadoop, Datastore, Firestore, Cloudera Data Platform, Big Query, Azure SQL, Cosmos DB, Red Shift, Apache Spark, ElastiCache, CloudSQL, Data Bricks, Snowflake, Apache Arrow, Apache Airflow, Flink.
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Engage in fast-paced client projects to plan, engineer, & design SCADA and communications systems. Automation Engineers design SCADA systems to address operational requirements & emerging trends including Smart Grid, Substation & Distribution Automation applications, Battery Energy Storage, and Microgrid controllers.
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Experience working with relational and NoSQL databases, as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage, Azure Blob Storage). Solid understanding of data engineering concepts, including data modeling, data processing pipelines, and big data technologies (e.g., Hadoop, Spark, Kafka.
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