28033 - MLOps Technician

Description

Job Summary: Design, automate, and maintain infrastructure and pipelines for AI solutions, collaborate on model productionization, and optimize DevOps and MLOps practices. Key Highlights: 1. Design and automation of infrastructure and pipelines in cloud environments 2. Collaboration with development and data science teams 3. Optimization of deployment processes and DevOps/MLOps practices A leading engineering and consulting firm specializing in sustainable mobility and digital transformation INCO has spent 55 years designing comprehensive, innovative, and technology-driven solutions that have advanced a new model of more sustainable and safer mobility. These solutions directly contribute to improving the quality of life for millions of people. With a multidisciplinary team of over 6\.000 professionals, the company operates across all continents, deploying its expertise and capacity to tackle technically complex projects through specialized knowledge and application of the most advanced and cutting-edge technologies. Responsibilities Design, automate, and maintain the infrastructure required for developing, training, and deploying AI solutions. Implement and manage infrastructure-as-code (IaC) using tools such as Terraform and Ansible, and design and operate continuous integration and continuous deployment (CI/CD) pipelines using tools like Jenkins. Collaborate with development and data science teams to facilitate AI model productionization, ensuring reproducible, scalable, and secure environments. Monitor platform operations, optimize deployment processes, and contribute to continuous improvement of DevOps and MLOps practices within the organization. Requirements Experience in: Designing, automating, and operating infrastructure and pipelines in cloud environments using DevOps and MLOps principles. Participation in building CI/CD pipelines for automated deployment of applications and AI models, as well as managing infrastructure-as-code (Terraform) and configuration automation (Ansible). Experience working with containers and orchestration, integrating continuous integration tools such as Jenkins, and operating systems in production environments—including monitoring, incident management, and deployment optimization. Familiarity with the machine learning model lifecycle in production, collaborating with development and data teams to ensure reproducible, scalable, and reliable deployments. // Years of experience in this role: \> 2 years // Qualifications: Computer Science \- Vocational Training \- Computer Science and Networks,Computer Science \- Bachelor's Degree in Computer Engineering,Computer Science \- Bachelor's Degree in Engineering and Data Systems,Computer Science \- Computer Engineering // Offered Offer