Senior ML Engineer | Germany (3 Month project)

Job description

We are looking for an experienced We are looking for an experienced ML Engineer / MLOps Engineer to join a cloud-native project for a German customer.

The role is strongly engineering-focused and involves building production-grade ML infrastructure, working with GPU workloads, ML pipelines, LLMs and large-scale data processing.

📍 Location: Germany 🗣 German: B2+ - must-have 🗣 English: B1+ 📅 Estimated start: September 30, 2026

What you'll be working on - Build and orchestrate ML pipelines using Kubeflow Pipelines (KFP v2) - Train ML models on GPUs and manage GPU resources within Kubernetes - Fine-tune transformers and LLMs - Track experiments and models using MLflow - Build classical ML models with XGBoost and CatBoost - Process large datasets using SQL Server and DuckDB - Develop Python-based pipelines, integrations and tooling - Maintain high engineering standards through testing, clean code and CI/CD with GitLab CI - Work in a secure, zero-trust / secure-by-default environment with network policies and restrictive container permissions

Requirements

What we're looking for - Hands-on experience with Kubeflow Pipelines, ideally KFP v2 - Experience training models on GPUs - Practical experience with LLM / transformer fine-tuning - Experience with MLflow - Strong knowledge of XGBoost, CatBoost or similar boosting models - Strong Python engineering skills - Solid SQL experience and understanding of large-scale data processing - Experience with CI/CD, clean code and automated testing - Production-grade ML/MLOps experience beyond notebook-based experimentation - Experience working in enterprise or regulated cloud-native environments

Nice to have - Experience with LLM pre-training, beyond fine-tuning - GPU orchestration in Kubernetes - Experience with zero-trust environments, network policies and restrictive container rights - Knowledge of DuckDB - Experience with modern Python tooling such as uv

Previous healthcare or billing domain experience is not required, but you should be comfortable quickly getting up to speed with a new domain.