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Show advanced knowledge of Machine Learning Algorithms/AI techniques including Deep Learning Techniques (RNN, CNN, GAN, etc) Demonstrate ability to work with a variety of Deep learning frameworks including TensorFlow, Keras, Caffe, CNTK, etc.
$104,000 - $150,000 a yearTemporaryRemoteExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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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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Applies a variety of methods based on standards and metrics to review and improve data acquisition and data management processes such as statistical analysis, machine learning, data mining, predictive analytics, time series analysis, multivariate regression analysis, statistical process control and optimization solutions.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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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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Because of our teams’ breadth of talent, we’ve been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and F1 EC2 Instances, in machine learning with AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Implement data processing pipelines using Azure Data Factory, Databricks, Azure Machine Learning, Azure Logic Apps, Azure Function Apps, Azure Kubernetes container and other big data services.
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We are interested in an energetic, experienced technology and field focused sales representative to demonstrate, sell and train on dirt simple construction software productivity tools, drone production tracking, 3D machine control modelling, and take-off software to heavy construction contractors.
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Job Title Big data Administrator Relevant Experience (in Yrs) Min 3-5 yrs Must Have Technical/Functional Skills " Proficiency in the Cloudera suite, including Kafka, HDFS, HBASE, KUDU, Zookeeper, HIVE, Impala, NIFI, SPARK, FLINK, Oozie, Yarn, Atlas, Ranger, RangerKMS, and KTS. " Experience with Cloudera ECS and Cloudera Data Services such as Cloudera Data Engineering, Cloudera Data Warehouse, and Cloudera Machine Learning.
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Relevant experience must be in one or more of the following (for Entry level) but in two or more for Full Performance, Senior, and Expert levels: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, computational science, software engineering, or data engineering.
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CUDA, Bash, and/or SQL), machine learning / deep learning methods, data analytics, and medical image analysis. Experience with common open-source scientific computing/machine learning libraries (e.g., PyTorch / TensorFlow), containerization, and cloud-native technologies (Docker & Kubernetes) is preferred.
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AI and Machine Learning, Azure Blobs, Office 365, Dynamic 365, Logic apps, Power apps, MS Flow, Power BI, Sharepoint o GitHub DevOps, CI/CD, workflows, actions and Ansible automations Skills Required : o Cloud solutions, design, architecture and security o Evaluating hardware.
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Statistical Background: Proficiency in statistics and machine learning techniques, particularly when applied to meteorological data. Within LSEG, the Power, Natural Gas, Coal, and Carbon Research division (formerly known as Point Carbon, Thomson Reuters, and Refinitiv) has a strong presence in the commodity community.
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Developing chatbot logic and algorithms using natural language processing (NLP) and machine learning techniques. Developing chatbot logic and algorithms using natural language processing (NLP) and machine learning techniques.
Part-timeExpandApply NowActive JobUpdated 6 days ago
machine learning jobs Title: intern Company: Seagate Technology in Houston, TX
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