ML/MLOps Engineer in Germany

Andersen is looking for an experienced ML/MLOps Engineer to join a project focused on building a cloud-native AI platform for the healthcare industry. You will be responsible for delivering scalable machine learning solutions and developing robust infrastructure in a secure, zero-trust environment.

Key responsibilities

• Building and orchestrating ML pipelines using Kubeflow Pipelines (KFP v2).
• Training models on GPUs and managing GPU resources within Kubernetes clusters.
• Fine-tuning transformers and LLMs while tracking experiments using MLflow.
• Developing classic machine learning models using XGBoost and CatBoost.
• Ensuring high code quality through rigorous testing and GitLab CI/CD practices.

Requirements

• Over 5 years of professional experience as an ML or MLOps Engineer.
• Hands-on expertise with Kubeflow Pipelines and GPU-based model training.
• Proven experience in fine-tuning LLMs and working with MLflow.
• Deep proficiency in Python and modern software engineering practices.
• Strong command of both English (Intermediate+) and German (Upper-Intermediate+).
• Experience working within regulated, enterprise-grade cloud-native environments.

What we offer

• Opportunity to work on cutting-edge AI and healthcare technology projects.
• Fully remote work environment with a focus on professional growth.
• Collaboration with a skilled team in a secure, zero-trust infrastructure setting.
• Exposure to modern data processing tools like DuckDB and advanced Python tooling.