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Knowledge and hands-on experience with DevOps tool chain such as Git, Jenkins, Nexus, Docker, Kubernetes, Harness etc. Intimately familiar with Azure and AWS cloud technologies. Ability to operate and drive projects and results in a DevOps model collaborating with both Operations and Development to streamline the integration and deployment process.
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C#, developer, devops, sdet, software engineer, software programmer. · Cloud technologies: Containers (Docker/Podman), Public cloud (GCP/AWS), Microservices. c#, developer, devops, sdet, software engineer, software programmer.
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That's why we need you, a Machine Learning (ML) Cloud and DevOps engineer, to help us shorten the time it takes to get critical tools developed and into the hands of our Agile developers creating AI products.
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As a business development manager for AWS GovCloud (US), you will have exciting opportunities to grow and expand the AWS GovCloud (US) customer and partner-base across US Department of Defense (DoD) and National Security.
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At least 8 years of organizational learning, facilitation and training experience working on complex international development programs, preferably in the sectors of agriculture, environment and/or food security.
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Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Quantum Research International, Inc. (Quantum) is a certified DoD Contractor providing services and products to US/Allied governments and industry in the following main areas: (1) Cybersecurity, High Performance Computing Systems, Cloud Services and Systems; (2) Space and Ground Support Systems; (3) Aviation Systems; (4) Missile Systems; (5) Artificial Intelligence/ Machine Learning Systems and Experimentation/Training; and (6) Audio Visual Systems and Services.
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Candidate will provide day-to-day management and oversight of DOT service delivery in areas such as SaaS/PaaS Implementation (notably Salesforce), Application/Software Development, Data Analytics and Visualization, Cloud Enablement, DevOps, Agile Transformation, Digital Modernization and Cybersecurity.
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Ideal candidate has knowledge in: Containerization, Cluster Administration, CI/CD Deployments, IAC’ed Bootstrap and Deployment ● Experience with Machine Learning Engineering (MLE); worked on deploying machine learning models and applications to Kubernete ● 6+ years working with AWS constructs, at least one major serverless application architecture/deployment.
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Our strong credentials include Global SAP Certified Provider of SAP BTP Operations, Global SAP Certified Provider of SAP Cloud and Infrastructure Operations, Global SAP Certified Provider of DevOps, Global SAP Certified Provider of SAP S/4HANA Solutions Operations, Global SAP Certified Provider of SAP SuccessFactors Solutions Operations, Global SAP Certified Provider of SAP HANA Operations, and Global SAP Certified Provider of SAP Business Suite Solutions Operations.
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This is a Cloud Network Engineer position that will be responsible for managing the configuration, installation and on-going support of the Network Infrastructure which includes PaloAlto firewalls, Cisco VPN Concentrators, Cisco CSR devices as well as Networking in cloud platforms such as AWS and Azure.
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CompTIA Security+ Certified Information System Security Processional (CISSP) Certified Information Security Manager (CISM) Certified Ethical Hacker (CEH) AWS Certified Cloud Practitioner (CCP) Microsoft Azure Google Cloud Platform (GCP.
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Experience working with the following tools: AWS, R or other Statistical Software, Python, and Statistical and Machine Learning Packages. Drive teams to utilize Machine Learning, AI or data mining and/or statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations, as well as identify opportunities to apply quantitative methods to improve business performance.
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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. Experience with AWS - S3, RDS.
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San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer.
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machine learning aws devops jobs Title: engineer Company: Pri in Washington, DC
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