Senior ML Engineer | Germany (3 Month project)

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.

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