ML/MLOps Engineer in Germany

Description

A European healthcare service provider delivers consulting, digital solutions, data-driven services, and operational support to help healthcare organizations improve efficiency, optimize processes, enhance service quality, manage resources, and adapt to evolving needs.

The project builds a cloud-native MLOps platform for the healthcare sector that supports large-scale machine learning and AI workloads. It includes ML infrastructure based on Kubeflow for LLM fine-tuning, traditional machine learning, and scalable data processing in a secure, zero-trust environment.

Responsibilities

• Build and orchestrate ML pipelines using Kubeflow Pipelines (KFP v2).
• Train models on GPUs and manage GPU resources within Kubernetes.
• Fine-tune transformers/LLMs and track experiments and models with MLflow.
• Build classic ML models using XGBoost and CatBoost.
• Work with data in SQL Server and DuckDB for efficient in-cluster processing of large datasets.
• Develop Python pipelines, integrations, and tooling based on uv.
• Ensure code quality through testing and CI/CD with GitLab CI.
• Work in a zero-trust, secure-by-default environment with network policies and restrictive container rights.

Requirements

• 5+ years of experience as an MLOps Engineer or ML Engineer.
• Hands-on experience with Kubeflow Pipelines (KFP v2).
• Experience training models on GPUs.
• Experience fine-tuning LLMs or transformers.
• Experience with MLflow model tracking.
• Experience with boosting models, including XGBoost and CatBoost.
• Deep proficiency in the Python ecosystem and modern engineering practices.
• Experience in regulated or enterprise cloud-native environments.
• Experience with SQL and large-scale data processing.
• CI/CD experience, preferably GitLab CI, plus clean-code and testing practices.
• Intermediate+ English.
• Intermediate+ German.

Nice to have

• LLM pre-training experience beyond fine-tuning.
• GPU orchestration experience in Kubernetes.
• Zero-trust environment experience, including network policies and restrictive container rights.
• DuckDB knowledge.
• Experience with modern Python tooling, including uv.

Benefits

• Work fully remotely, from an office, or in a hybrid arrangement.
• Mentoring and onboarding support.
• Opportunity to earn up to an additional USD 1,000 per month, included in the annual bonus, depending on expertise and participation in company activities.
• Access to a corporate training portal.
• Certification compensation for AWS, PMP, and other certifications.
• Referral program.
• Private health insurance and sports-activity compensation.