Senior Machine Learning Engineer

Quick Facts

• Role: Senior Machine Learning Engineer

• Focus: cloud-based Machine Learning and Generative AI for core insurance processes

• Work style: hybrid with presence in Coburg

Description

You will design and implement cloud-based AI solutions—including machine learning, generative AI, and agent systems—for key processes such as claims, pricing, and customer service. The role includes productive deployment of scalable ML and GenAI workloads, working closely with MLOps colleagues, and helping shape the ML/AI tool stack. You will also define engineering standards and mentor teammates with a strong end-to-end responsibility from data to operations.

Responsibilities

• Concept and implement cloud-based AI solutions (ML, Generative AI, agent systems) for core processes like claims, pricing, and customer service

• Enable productive, scalable deployment of ML and GenAI workloads in close collaboration with MLOps

• Select and introduce modern architectures and tooling for ML workflows; actively co-design the Data Science and AI tool stack

• Design and implement standards and best practices for Machine Learning Engineers and Data Scientists

• Mentor, perform reviews, and coach—especially on cloud topics—with end-to-end responsibility from data to operations

• Collaborate in an interdisciplinary team with Data Scientists, Machine Learning Engineers, and domain/IT experts

Requirements

• Degree (Master at minimum, Promotion ideal) in Data Science, Machine Learning, Mathematics, Physics, Computer Science, or a related field

• Several years of hands-on experience as an ML/AI Engineer, ideally as a Senior with project responsibility

• Strong practical/theoretical ML engineering knowledge

• Experience with container and cloud-native ML engineering tools and practices (Docker, Kubernetes, IaC, CI/CD) plus ML workflow tooling (MLflow, Airflow) and AWS services (e.g., S3, Step Functions, Lambda, SageMaker, Bedrock)

• Strong communication skills to explain complex technical concepts clearly

• Independent, goal-oriented working style with high ownership for projects and results

• Willingness to work in a hybrid model with on-site presence in Coburg

Benefits

• Flexible working arrangements

• Extensive professional development opportunities

• Numerous employee benefits

• Support for work-life balance and family compatibility

• Health and well-being support