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Seattle, United States Google India Pvt Ltd Full timeApply for Staff Software Engineer, Infrastructure, Google Cloud Compute, Career Progress Consultants in Seattle for 5 - 8 Year of Experience on TimesJobs.com.
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Cloud Infrastructure Engineer
2 months ago
About the team
We are seeking a highly skilled Cloud Infrastructure Engineer with expertise in Cloud Computing on AWS, running workloads in Kubernetes, and a focus on ML Ops and other Data Engineering workloads. This is a challenging and exciting opportunity for a highly motivated and skilled Cloud Infrastructure Engineer to join our team and work on cutting-edge technologies as we build self-serving data platforms. The ideal candidate will have a solid foundation in cloud infrastructure, containerization, and automation, as well as experience in designing, deploying, and maintaining complex systems. Additionally, proficiency in data engineering, machine learning, and data pipelines will be essential for success in this role. If you are passionate about cloud computing, Kubernetes, and ML Ops or other data engineering workloads, we encourage you to apply.
What you’ll do
Assist in designing, deploying, and maintaining cloud infrastructure on AWS
Contribute to the management and optimization of Kubernetes clusters for running workloads
Participate in the development and maintenance of CI/CD pipelines for deploying applications
Contribute to the development and maintenance of data pipelines for ML Ops or other data engineering workloads
Collaborate with senior engineers, data scientists, and engineers to support the design and deployment of ML models
Assist in monitoring and troubleshooting system performance and availability
Contribute to the automation of infrastructure and application deployments
Stay informed about emerging technologies and industry trends
Who you are
Bachelor's degree in Computer Science or related field
2+ years of experience in cloud computing on AWS
1+ years of experience in Kubernetes and container orchestration
Exposure to ML Ops or other data engineering workloads
Experience building or maintaining data or ML deployment pipelines in a cloud environment
Proficiency in object oriented design principles (Python and Go preferred)
Basic experience in automation and infrastructure as code
Strong problem-solving skills and attention to detail
Excellent communication and collaboration skills
Strong understanding of complex distributed systems
Experience with monitoring and alerting systems
Preferred Qualifications
Master's degree in Computer Science or related field
AWS/Kubernetes certification (preferred but not required)
Experience using Terraform, Docker or other containerization technologies, Helm, data visualization and dashboarding tools, or other infrastructure as code tools
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