Machine Learning Engineer – MLOps & AI

The successful candidate will integrate, deploy, and operate machine learning and AI solutions for digital products, data platforms, and applications across the company and within the R&D environment.
They will ensure that machine learning models and AI components based on process, equipment, product, and business data can be developed reproducibly, integrated reliably, and operated in production.
In doing so, they will make a significant contribution to building a scalable Data & AI foundation and delivering data-driven R&D products and internal AI applications.

• Independently implement, operate, and maintain machine learning and AI solutions for digital products and operational use cases
• Transform machine learning models and prototypes into stable, scalable, and production-ready software solutions
• Develop and maintain training, validation, deployment, and inference pipelines for machine learning models
• Prepare and integrate data, models, and AI services into existing applications, platforms, and business processes
• Contribute to the development of standardized ML and AI platforms, reusable components, and consistent MLOps and AI engineering patterns
• Ensure model quality, reproducibility, traceability, monitoring, and the technical maintainability of the ML and AI solutions within your area of responsibility
• Perform and automate model testing, performance analysis, versioning, and continuous model updates
• Support the evaluation of new AI and machine learning use cases with regard to technical feasibility, data availability, scalability, and production readiness
• Collaborate with data engineering, software development, cloud and platform engineering, data science, process engineering, domain experts, and IT teams

• Strong knowledge of developing, training, validating, and deploying machine learning and AI models in production
• Solid knowledge of statistical modelling and established supervised and unsupervised machine learning methods, including regression, classification, clustering, ensemble methods, and time-series analysis
• Strong knowledge of building automated training, inference, and deployment pipelines, as well as managing the complete model lifecycle
• Experience with model versioning, experiment tracking, reproducibility, traceability, and model monitoring
• Strong proficiency in Python, PySpark/Spark, MLflow, and Kubernetes, as well as commonly used machine learning, analytics, and development tools
• Experience integrating machine learning models and AI services through APIs, interfaces, and suitable model-serving technologies
• Experience with databases, data formats, data integration, and the processing of both structured and unstructured data
• Basic understanding of modern cloud, container, and platform architectures
• Knowledge of data and model quality, data validation, automated testing, technical documentation, and monitoring
• Knowledge of fundamental software engineering principles, particularly version control, testing, CI/CD, and modular software development
• Ability to translate business requirements and AI use cases into structured, scalable, and maintainable machine learning solutions
• Desirable: Experience with feature stores, model serving, GPU-based workloads, and generative AI applications

• Willingness and ability to learn and become proficient in new technologies
• Analytical and structured approach to work
• Initiative and a strong sense of responsibility
• Ability to identify opportunities for innovation and optimization
• Strong teamwork and collaboration skills in interdisciplinary and international environments
• Excellent written and spoken English, with the ability to communicate effectively with colleagues and stakeholders in Germany
• German language skills are an advantage but not required
• Clear communication tailored to different audiences
• Reliability, pragmatism, and a strong commitment to quality

• Bachelor’s degree in computer, Information Systems or related specialization in IT
• 5 to 8 years of relevant experience.