Continental
Automotive
MLOpsEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“ML Ops Engineer at Continental. Skills: ML Ops, Python, CI/CD, Cloud Platforms. Design CI/CD pipelines for ML models. Build scalable ML infrastructure”
What You'll Achieve.
Transform machine learning into scalable, production-ready solutions; Ensure seamless integration of models into production environments; Optimize model performance at scale; Enable AI-driven insights
Industry & Context.
What They're Looking For.
Must Have
2+ years of working experience as a ML Ops, programming skills in Python, Practical knowledge in CI/CD and automation tools, Proficiency in containerization and orchestration, Hands-on experience with ML model deployment and lifecycle management, Good knowledge of cloud platforms, infrastructure-as-code, Solid understanding of software engineering and DevOps practices, Experience with Agile project management methods
Nice to Have
Familiarity with monitoring and performance tracking tools, workflow orchestration
What You'll Do.
Design CI/CD pipelines for ML models
Build scalable ML infrastructure
Implement monitoring and feedback loops
Collaborate with data scientists and engineers
How You'll Work.
Team & Collaboration
Collaborate with data scientists and engineers; Work with cross-functional teams
Communication Scope
Proficient English language skills
Process & Methodology
Scrum, Kanban
Full Job Description
Continental is a leading tire manufacturer and industry specialist that develops and produces sustainable, safe and convenient solutions for automotive manufacturers as well as industrial and end customers worldwide. Founded in 1871, the company generated sales of €19.7 billion in 2025 and currently employs around 78,000 people in 54 countries and markets. In Digital Solutions, we drive innovation for connected mobility and deliver cutting-edge digital products to our global fleet customers. As a ML Ops 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. Key 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. ## Qualifications * Academic degree in Science, Engineering, Mathematics or any related field; * 2+ years of working experience as a ML Ops Engineer; * Strong programming skills in Python and SQL; * Practical knowledge 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; * Famil
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