Senior MLOps Engineer – Digital Solutions

About the role

Continental’s Digital Solutions Department is looking for an experienced MLOps Engineer to help turn machine‑learning models into reliable, production‑ready services. You will work with data scientists, data engineers and cross‑functional teams to deliver AI‑driven insights that improve mobility safety, efficiency and sustainability worldwide.

Key responsibilities

• Design, implement and maintain CI/CD pipelines that move ML models from development to production.
• Build and operate scalable ML infrastructure on cloud platforms using infrastructure‑as‑code.
• Automate deployment, monitoring, rollback and reproducibility processes.
• Set up monitoring and feedback loops to track model performance and drive continuous improvement.
• Collaborate with data scientists and engineers to integrate models and standardise workflows.
• Provide technical leadership, mentorship and promote best practices across the team.

Required profile

• Academic degree in Computer Science, IT, Engineering, Mathematics or a related field.
• More than three years of professional experience as an MLOps Engineer.
• Strong programming skills in Python and SQL.
• Proficiency in CI/CD and automation tools such as GitHub Actions.
• Experience with containerisation and orchestration (Docker, Kubernetes).
• Hands‑on experience with ML model deployment and lifecycle management tools (MLflow, SageMaker).
• Good knowledge of cloud platforms (AWS or Azure) and infrastructure‑as‑code practices.
• Familiarity with monitoring tools (Grafana) and workflow orchestration (Airflow).
• Solid understanding of software engineering and DevOps practices.
• Experience with Agile methodologies (Scrum, Kanban) and fluent English communication.

Required skills

• Python
• SQL
• GitHub Actions
• Docker
• Kubernetes
• MLflow
• SageMaker
• AWS
• Azure
• Grafana
• Airflow