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Responsibilities:
Collaborate with software development team to understand the software system requirements and design, build, and maintain the deployment pipeline using Continuous Integration and Continuous Deployment (CI/CD) methodologies.
Manage and maintain the AWS infrastructure including provisioning, scaling, monitoring and troubleshooting.
Develop and maintain automation tools and scripts for the deployment, configuration, and maintenance of the software systems.
Contribute to the development of Machine Learning models and deploy them in production using containerization technologies such as Docker.
Implement security best practices and ensure compliance with industry standards and regulations.
Work with the development team to optimize the software systems for scalability, reliability, and performance.
Monitor the performance of the software systems and take proactive measures to ensure high availability and fault-tolerance.
Stay up-to-date with emerging technologies and trends in DevOps, Machine Learning and AWS.
Requirements:
Bachelor’s or Master’s degree in Computer Science or a related field.
Proven experience as a DevOps Engineer with experience in Machine Learning and AWS.
Strong programming skills in languages such as Python, Java, and/or Go.
Experience with containerization technologies such as Docker and container orchestration platforms such as Kubernetes.
Strong understanding of CI/CD methodologies and experience with tools such as Jenkins, GitLab or CircleCI.
Experience with cloud infrastructure platforms such as AWS, Azure, or Google Cloud Platform.
Familiarity with Machine Learning frameworks such as TensorFlow, Keras, and PyTorch.
Experience with monitoring and logging tools such as Prometheus, Grafana and Elasticsearch.
Strong problem-solving and analytical skills, with excellent attention to detail.
If you meet the above requirements and are passionate about DevOps, Machine Learning and AWS, we would love to hear from you. Please send us
