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Bachelor's degree or higher in machine learning, data science, statistics, computer science, economics, mathematics, information systems, or similar field preferred. Experience using tools such as Azure's Machine Learning and Cognitive Services; AWS's SageMaker, Polly and Rekognition; DataRobot; or H2O.ai.
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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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Design, develop, and implement machine learning models, focusing on Model Deployment, MLOps processes, Model monitoring, Data and Model drift detection. Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or a related field.
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Preference is for candidates with experience with common open source scientific computing/machine learning libraries including: scipy, pandas, statsmodel, OpenCV, XGBoost, PyTorch / TensorFlow.
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The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter environment.
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We have created software to help college students in three of those subjects read with more engagement and practice more effectively, incorporating our research team’s expertise in cognitive science and machine learning.
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Participate in the design of pathology/biological/sequencing experiment to generate high quality data for machine learning. Develop and maintain computational methods using deep learning for pathological image processing.
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Familiarity with relevant technology, such as Big Data (Hadoop, Spark, Hive, BigQuery); Data Warehouses; Business Intelligence; and Machine Learning. 7+ years of direct sales experience carrying and exceeding a quota and selling enterprise software/ software-as-a-service (Business Intelligence/ Data Warehouse/ Big Data/ Advanced Analytics/ Machine Learning) to C-level executives.
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Evaluate and recommend AI technologies, focusing on OCR, NLP, LLM and machine learning. Expertise in OCR, NLP, LLM and other machine learning techniques. BigRio is a Digital Transformation consulting firm headquartered in Boston, MA, specializing in data and analytics, custom development, software implementation, data analytics, and machine learning/AI integrations.
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Our specialized HPC and digital technologies support our advanced and secure cloud-based workflows, expert geoscience data transformation and AI, machine learning and data science services.
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Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) As a Software Engineer III at JPMorgan Chase within the Corporate Sector, Regulatory Controls and Operational Risk Technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way.
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Technologies: Dynamics 365, Common Data Model, Microsoft 365, Microsoft PowerApps, Microsoft Flow, Microsoft Azure, PowerBI, Azure IoT Suite, Azure Machine Learning, Artificial Intelligence.
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Employees in this role use knowledge of machine learning, optimization, statistics, and applied mathematics along with abilities in software engineering with a focus on distributed computing and data storage infrastructure (e.g. “Big Data.
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Statistical Background : Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data. You will experience the critical role we have in helping to re-engineer the financial ecosystem to support and drive sustainable economic growth.
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Robotics, Autonomy, Defense, Perception, Artificial Intelligence, AI, Technology, Engineering, Hardware, Software, Drones, UAV, UAS, Machine Learning, and National Security. Work in collaboration with our DevOps teams to architect and maintain our cloud infrastructure, working with containerization technologies such as Docker and Kubernetes; assist with cross-platform builds and test orchestration, working with build tools (e.g. CMake, Bazel, etc.
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machine learning jobs Title: devops engineer in Houston, TX
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