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.

Originally posted on Himalayas