Integration and Deployment: - Implement continuous software integration and deployment using DevOps best practices. - Design, configure, and manage robust CI/CD pipelines to facilitate continuous delivery and integration of ML projects and other software products. Automation: - Automate development, testing, deployment and operation tasks (monitoring, support, availability, etc.) of products. - Develop scripts and tools for the automation of recurring processes and optimization of workflows. Compliance with Deadlines: - Deliver their work on the dates to which they are committed. - Communicate in a timely manner any inconvenience that prevents the fulfillment of deadlines and objectives of the project. Continuous Improvement: - Generate and fulfill commitments for the continuous improvement of their skills. - Evaluate and adopt new technologies and methodologies that can improve the efficiency and quality of work. Best Practices: - Apply best practices in deliverables. - Promote and ensure the implementation of safety and quality standards in all processes. Quality: - Respond for the quality of the tasks performed. - Carry out code reviews and technical audits to ensure the quality and stability of what is built. Software Testing: - Participate in software testing and be responsible for the functionalities developed. - Develop and maintain automated test environments to ensure the reliability and performance of the software. Product Integration: - Collaborate with the integration of various products related to the software in charge. - Coordinate with other development teams to ensure compatibility and efficient integration of the systems. Collaboration and Participation: - Active and punctual participation in the activities of their work team. - Foster a culture of collaboration and effective communication within the team and with other departments. Infrastructure Management: - Manage and optimize cloud infrastructure (AWS) and on-premise infrastructure, ensuring scalability and efficiency. - Implement configuration and version management policies to maintain consistency and traceability of changes. - Manage and maintain cloud resources, including compute, networking, storage, and database instances. Security and Compliance: - Ensure that all processes and tools comply with the company's security policies and regulations. - Implement DevSecOps practices to integrate security into all phases of the software development lifecycle. Mentoring and Support: - Provide mentoring and support to other team members, sharing knowledge and promoting professional development. - Act as a technical reference in projects, guiding the team towards the implementation of efficient and effective solutions. Cost Optimization: - Monitor and optimize the use of cloud resources to ensure efficient and cost-effective use of infrastructure. - Implement cost-saving strategies without compromising performance or security. Technical Documentation: - Contribute to the creation and maintenance of technical documentation to ensure that the implemented solutions are understandable and reproducible. - Document operational procedures and standards to facilitate knowledge and training within the team. Collaboration with Research and Development Areas: - Work closely with research and development areas to understand how products are built, designed and operated. - Design and implement development, automation and testing tools for software projects. ML Lifecycle Management: - Monitor processes throughout the lifecycle to ensure adherence, updating or creating new processes to improve and minimize waste. - Manage code deployments, fixes, updates, and related processes. Code Review and Validation: - Use advanced technical skills to review, verify, and validate the code of Python projects. - Develop systems and pipelines for the ingestion and transformation of multiple data sources. Microservices Deployment and Management: - Manage the deployment and administration of microservices, ensuring their integration and efficient operation. Monitoring and Support: - Configure and maintain monitoring systems to ensure availability and optimal performance of services. - Respond and resolve incidents proactively, ensuring service continuity. Academic Background Postgraduate (Optional, can be substituted for experience): Specialization in Software Engineering. Specialization in DevOps. Specialization in Cloud Infrastructure Management. Master in Software Engineering. Master in DevOps. Master in Cloud Infrastructure Management. Related areas. Alternatively: Two additional years of relevant experience in lieu of postgraduate study. Professional Certifications (Optional, but valued): AWS Certified DevOps Engineer Certification. Google Professional DevOps Engineer Certified. Microsoft Certified: Azure DevOps Engineer Expert Certification. Kubernetes Administrator (CKA) certification. Certification in CI/CD tools (Jenkins, GitLab CI/CD, CircleCI). Certification in agile methodologies (Scrum Master, Agile Practitioner). Additional Knowledge: Courses and training in MLOps. Specialization courses in automation and configuration management tools (Terraform, Ansible, Chef, Puppet). Specialization courses in containers and orchestrators (Docker, Kubernetes). Experience Minimum experience of 7 years in similar roles: Integration and Continuous Deployment: Management of the integration and continuous deployment of software in hybrid environments (cloud and on-premise). Scripting Languages: Advanced scripting proficiency with Bash, Python, Ruby, Perl for task automation and workflow optimization. DevOps Practices: Deep experience in DevOps best practices, including designing, configuring, and managing robust CI/CD pipelines for continuous delivery and continuous integration. Monitoring and Troubleshooting: Proven ability to monitor cloud and on-premise applications and platforms, create metrics, dashboards, and alerts to ensure availability and optimal performance of services. Containerization and Cloud Technologies: Experience in containerization technologies such as Docker and orchestration with Kubernetes. Hands-on Experience in Cloud Platforms: Experience in managing cloud infrastructure (AWS, Azure, GCP). Configuration Management and Automation: Configuration management expertise with tools such as Terraform, Chef, Puppet, Ansible, or similar to maintain consistency and traceability of changes. Linux Systems Administration: Senior experience in Linux systems administration, including infrastructure optimization and efficient resource management. Collaboration and Continuous Improvement: - Demonstrated ability to collaborate effectively with development teams and other areas, promoting a culture of collaboration and effective communication. - Commitment to continuous improvement through the adoption of new technologies and methodologies that improve the efficiency and quality of work. Security and Compliance: Implementation of DevSecOps practices to integrate security into all phases of the software development lifecycle, ensuring compliance with security policies and regulations. Technical Documentation and Mentoring: - Active contribution to technical documentation to ensure reproducibility and understanding of implemented solutions. - Experience in providing mentoring and technical support to other team members, sharing knowledge and promoting professional development. Experience in Machine Learning Projects: Practical experience in Machine Learning projects, including the automation and optimization of ML model development and deployment processes. MLOps Pipeline Implementation and Management: Experience in the development, implementation, and management of MLOps pipelines for the training, deployment, and monitoring of Machine Learning models. #J-18808-Ljbffr