ML Ops Engineer - Digital Solutions

Responsibilities

• ▹Design and manage CI/CD pipelines for ML models from development to production
• ▹Build and maintain scalable ML infrastructure on cloud platforms using infrastructure-as-code
• ▹Automate deployment, monitoring, and rollback processes for reliability and reproducibility
• ▹Implement monitoring and feedback loops for model performance and continuous improvement
• ▹Collaborate with data scientists and engineers to integrate ML models and standardize workflows

Requirements

• ▹Academic degree in Science, Engineering, Mathematics, or a related field
• ▹2+ years of working experience as an ML Ops Engineer
• ▹Strong programming skills in Python and SQL
• ▹Practical knowledge of CI/CD and automation tools (e.g., GitHub Actions)
• ▹Proficiency in containerization and orchestration (Docker, Kubernetes)
• ▹Hands-on experience with ML model deployment and lifecycle management (MLflow, SageMaker)
• ▹Good knowledge of cloud platforms (AWS or Azure) and infrastructure-as-code practices
• ▹Familiarity with monitoring and performance tracking tools (Grafana) and workflow orchestration (Airflow)
• ▹Solid understanding of software engineering and DevOps practices (testing, GitOps, CI/CD design patterns)
• ▹Experience with Agile project management methods (Scrum, Kanban)
• ▹Reliable team player with a structured, self-organized work style
• ▹Proficient English language skills (written and spoken)

Soft skills

What we offer

• ▹Integration into a challenging, international work environment
• ▹Flexible working model
• ▹Agile and collaborative working style
• ▹Continuous opportunities for personal development and learning

About the company

Continental is a leading tire manufacturer and industry specialist that develops and produces sustainable, safe, and convenient solutions for automotive, industrial, and end customers worldwide. Founded in 1871, it generated sales of €19.7 billion in 2025 and employs around 78,000 people in 54 countries.