Senior Machine Learning Engineer

Quick Facts

Senior Machine Learning Engineer focused on building and operating production-grade Machine Learning systems in an enterprise environment.

Description

You will design and implement scalable ML architectures for highly available enterprise applications and build robust data, training, and deployment pipelines with clear CI/CD integration. You’ll operate productive systems by implementing monitoring, drift detection, and retraining, and you’ll optimize models based on latency, scalability, and resource efficiency. The role requires strong MLOps expertise and professional communication in German and English.

Responsibilities

• Design and implement scalable ML architectures for highly available enterprise applications
• Build robust data, training, and deployment pipelines with clear CI/CD integration
• Implement monitoring, drift detection, and retraining mechanisms for production systems
• Analyze latency, scaling behavior, and resource efficiency and optimize models accordingly
• Make technical decisions in ML projects and collaborate with platform and DevOps teams

Requirements

• At least five years’ experience developing and operating productive Machine Learning systems in an enterprise environment
• Degree in Computer Science, Software Engineering, Data Science, or a comparable technical field
• Expert knowledge of MLOps principles including model versioning, Feature Stores, and lifecycle management
• Experience with Python, Docker, Kubernetes, MLflow, and at least one hyperscaler cloud (AWS, Azure, or GCP)
• Engineering-oriented, test-driven approach with focus on scalability and stability
• Ability to apply AI tools, critically evaluate results, and support customers in realizing AI potential
• Fluent professional communication in German and English

Benefits

• Growth opportunities via challenging projects, interdisciplinary teams, and targeted training programs
• Culture based on openness, ownership, and shared success