Senior ML Ops Engineer

About the role

Join Continental’s Digital Solutions Department as an MLOps Engineer. You will transform machine‑learning prototypes into scalable, production‑ready solutions that power smarter, safer mobility for global fleet customers. The role combines software engineering, cloud infrastructure, and data science collaboration.

Key responsibilities

• Design, implement and maintain CI/CD pipelines that move ML models from development to production.
• Build and manage scalable ML infrastructure on cloud platforms using infrastructure‑as‑code.
• Automate deployment, monitoring, rollback and feedback loops to ensure model reliability and 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, Engineering, Mathematics or related field.
• More than 3 years of professional experience as an MLOps Engineer.
• Strong programming skills in Python and SQL.
• Experience with CI/CD and automation tools such as GitHub Actions.
• Proficiency in containerisation and orchestration (Docker, Kubernetes).
• Hands‑on experience with ML model deployment tools (MLflow, SageMaker).
• Good knowledge of cloud platforms (AWS or Azure) and IaC practices.
• Familiarity with monitoring tools (Grafana) and workflow orchestration (Airflow).
• Solid understanding of software engineering and DevOps practices.
• Fluent English, both spoken and written.

Required skills

• Python
• SQL
• GitHub Actions
• Docker
• Kubernetes
• MLflow
• SageMaker
• AWS
• Azure
• Infrastructure‑as‑code
• Grafana
• Airflow
• Git
• CI/CD design patterns

What we offer

• Integration in a challenging, international work environment.
• Flexible working model.
• Agile and collaborative working style.
• Continuous opportunities for personal development and learning.
• Inclusive workplace where all applications are welcome.