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E.g. Docker, Podman, Kubernetes, K3S, Rancher)' Hands on experience with Amazon Web Services, Google Cloud Platform, or Azure; namely choosing platform components and assembling application and runtime architecture.
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All Positions are open for all visas and US citizens We at Synergisticit understand the problem of the mismatch between employer's requirements and Employee skills and that's why since 2010 we have helped thousands of candidates get jobs at technology clients like Apple, Google, and Paypal, western union, Client, visa, Walmart labs, etc., to name a few.
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Imubit has combined the industry expertise from companies like Exxon and Shell with award-winning data scientists endorsed by Google. Advanced CI and DevOps technologies - Kubernetes, Docker, Jenkins.
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They are searching for a Data Engineer with a particular focus on Google Cloud Platform to join their team. Kubernetes / Docker. Google Cloud Platform. Data Engineer / Python Data Engineer.
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Spring boot, Microservices, Docker, Jenkins, Github, Kubernates and REST API's experience. We at Synergisticit understand the problem of the mismatch between employer's requirements and Employee skills and that's why since 2010 we have helped 1000's of candidates get jobs at technology clients like apple, google, Paypal, western union, Client, visa, walmart lab s etc to name a few.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud. Hands-on experience with containerization and orchestration tools (e.g., Docker, Kubernetes). Implement and manage infrastructure as code (IaC) using tools like Terraform or CloudFormation.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. Design and implement containerized solutions using Docker, Kubernetes, or other containerization technologies.
ExpandApply NowActive JobUpdated 18 days ago - UpvoteDownvoteShare Job
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Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or Google Cloud Platform). Experience containerizing analytical models using Docker and Kubernetes or other container orchestration platforms.
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Experience with automation tools and frameworks, such as Jenkins, GitLab CI/CD, Ansible, Terraform, Docker, Kubernetes, and/or Chef/Puppet. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and serverless architectures is a plus.
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2+ years of experience working with container technologies (Docker, Kubernetes, or Helm) Experience with UI/UX analytics platforms for engagement analysis (Amplitude, Mixpanel, Google Analytics.
$225,750 - $271,250 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Relevant certifications (e.g., AWS Certified Solutions Architect, Google Cloud Certified - Professional Cloud Architect) are a plus. In-depth knowledge of software architecture principles, microservices architecture, containerization (e.g., Docker, Kubernetes), and distributed computing.
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Proficiency with cloud technologies such as AWS, Azure, and Google Cloud Platform; familiarity with serverless architectures, Docker, and Kubernetes. Proficiency with cloud technologies such as AWS, Azure, and Google Cloud Platform; familiarity with serverless architectures, Docker, and Kubernetes.
$145,000 - $182,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience working with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes). 1+ years of experience to have knowledge of Docker, Jenkins, Kubernetes, and other DevOps tools.
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Exposure to CI/CD/DevOps, Terraform, Docker and monitoring technologies. Strong experience in backend Java Ability to learn, adapt and collaborate with various programming languages (Rust, Go, Javascript)Comfortable in a fast-paced environment focused on delivering production code at a regular cadence using Agile techniques, tools, and methodologies.
$102,000 - $128,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Experience in container management systems (Amazon ECS, Docker, Kubernetes) · Commercial experience in the architecture, development, and deployment of cloud infrastructure for production AI/ML inference (AWS, Azure, Google Cloud, etc.
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