(Senior) ML Ops Engineer
This role focuses on architecting and maintaining end-to-end ML pipelines for Continental’s digital mobility solutions, ensuring seamless model deployment and performance optimization in production environments. You’ll collaborate with data scientists and engineers to bridge AI innovation with scalable, real-world applications in connected mobility.
Skills required
About this role
Join Continental’s Digital Solutions Department as a MLOps Engineer
In Digital Solutions, we drive innovation for connected mobility and deliver cutting-edge digital products to our global fleet customers. As a MLOps Engineer, you will be at the forefront of transforming machine learning into scalable, production-ready solutions.
You will design, deploy, and maintain robust ML pipelines, ensuring seamless integration of models into production environments and optimizing their performance at scale. Working closely with Data Scientists, Data Engineers, and cross-functional teams, you will enable AI-driven insights that power smarter, safer, and more efficient mobility worldwide.
Main 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;
- Provide technical leadership and mentorship, fostering knowledge sharing and best practices.
Qualifications
- Academic degree in Computer Science, IT, Engineering, Mathematics, or related field;
- >3 years of professional experience as a MLOps Engineer;
- Strong programming skills in Python and SQL;
- Expertise in 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);
- Experience working in an international team (desirable);
- Proficient English language skills (spoken / written).
Additional Information
Our offer:
- Integration in a challenging and international work environment;
- Flexible working model;
- Agile and collaborative working style;
- Continuous opportunities for personal development and learning.
We are committed to fostering a workplace where everyone feels safe, respected, and valued. All kind of applications are welcome.
Ready to drive with Continental? Take the first step and fill in the online application.
