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
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Build and orchestrate ML pipelines using Kubeflow Pipelines (KFP v2)
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Train ML models on GPUs and manage GPU resources within Kubernetes
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Fine-tune transformers and LLMs
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Track experiments and models using MLflow
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Build classical ML models with XGBoost and CatBoost
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Process large datasets using SQL Server and DuckDB
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Develop Python-based pipelines, integrations and tooling
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Maintain high engineering standards through testing, clean code and CI/CD with GitLab CI
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Work in a secure, zero-trust / secure-by-default environment with network policies and restrictive container permissions
Requirements
What we’re looking for
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Hands-on experience with Kubeflow Pipelines, ideally KFP v2
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Experience training models on GPUs
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Practical experience with LLM / transformer fine-tuning
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Experience with MLflow
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Strong knowledge of XGBoost, CatBoost or similar boosting models
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Strong Python engineering skills
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Solid SQL experience and understanding of large-scale data processing
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Experience with CI/CD, clean code and automated testing