Andersen is hiring an ML/MLOps Engineer in Germany for a project building a cloud-native AI platform and delivering scalable machine learning solutions for the healthcare industry.
The project is focused on building a cloud-native MLOps platform for the healthcare sector to support large-scale machine learning and AI workloads. It includes developing ML infrastructure based on Kubeflow, enabling LLM fine-tuning, traditional machine learning, and scalable data processing in a secure, zero-trust environment.
Responsibilities:
- Building and orchestrating ML pipelines using Kubeflow Pipelines (KFP v2).
- Training models on GPUs, including GPU resource management within Kubernetes.
- Fine-tuning transformers/LLMs, tracking experiments and models via MLflow.
- Building classic ML models (XGBoost, CatBoost).
- Working with data using SQL Server and DuckDB as a lightweight OLAP solution for efficient in-cluster processing of large datasets.
- Developing in Python (pipelines, integrations, tooling based on uv).
- Ensuring code quality: testing, CI/CD (GitLab CI).
- Working within a zero-trust / secure-by-default environment (network policies, restrictive container rights).
Kogo poszukujemy?
Must-haves:
- Experience as a MLOps Engineer / ML Engineer for 5+ years.
- Hands-on experience with Kubeflow Pipelines (KFP v2).
- Experience training models on GPUs.
- Experience fine-tuning LLMs/transformers.
- Experience with MLflow (model tracking).
- Experience with boosting models (XGBoost, CatBoost).
- Deep proficiency in the Python ecosystem and modern engineering practices.
- Experience working in regulated/enterprise cloud-native environments.
- Experience with SQL and large-scale data processing.
- CI/CD experience (GitLab CI preferred), clean code and testing practices.
- Level of English – from Intermediate+ or above.
- Level of German – from Upper-Intermediate or above.
Nice-to-haves:
- Pre-training experience for LLMs (beyond fine-tuning).
- Experience with GPU orchestration in Kubernetes.
- Experience in zero-trust environments (network policies, restrictive container rights).
- Knowledge of DuckDB.
- Experience with modern Python tooling (uv).
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ML/MLOps Engineer in Germany Arbeitgeber: HeadHR
Als Arbeitgeber bieten wir Ihnen die Möglichkeit, in einem dynamischen und innovativen Umfeld zu arbeiten, das auf die Entwicklung von Testautomatisierungsframeworks spezialisiert ist. Unsere flexible Arbeitsweise, sei es hybrid in Wrocław oder vollständig remote, ermöglicht es Ihnen, Ihre Arbeitszeiten selbst zu gestalten und eine ausgewogene Work-Life-Balance zu erreichen. Zudem fördern wir aktiv die berufliche Weiterentwicklung unserer Mitarbeiter durch Schulungen und den Einsatz neuester Technologien im Bereich AI/ML.
