Senior MLOps/AI Engineer

Your responsibilities:

• Build and maintain end-to-end MLOps / LLMOps pipelines (CI/CD, monitoring, retraining).

• Deploy, scale, and operate high-availability APIs and model-serving services for anomaly detection and predictive data quality scoring.

• Integrate advanced AI tools (e.g., LangChain, Portkey, Galileo, HuggingFace Transformers) into data quality agents and automated error-classification workflows.

• Collaborate with Data Engineering and IT Ops teams to manage AWS-based infrastructure for scalable model serving and monitoring.

• Implement comprehensive performance, drift, and data-quality monitoring with automated retraining loops.

• Ensure all AI systems comply with internal security guidelines and GxP requirements.

We are looking for you, if you have:

• Proven experience as an AI Engineer, ML Engineer, or MLOps Engineer in production environments.

• Strong expertise with MLOps platforms (AWS SageMaker, Kubeflow, MLflow).

• Advanced Python skills and ability to deliver robust, tested production code.

• Hands-on experience with Docker and Kubernetes.

• Experience deploying Transformer or LLM-based models (HuggingFace, LangChain).

• Solid knowledge of AWS services (Lambda, EC2, SageMaker).

• Strong understanding of system design, distributed computing, and data streaming.

Nice to Have

• Experience in regulated GxP environments.

• Familiarity with Pharmacovigilance (PV), clinical trial data, or Master Data Management.

We offer:

• Participation in interesting and challenging projects.

• Flexible working hours.

• A great, non-corporate atmosphere.

• Opportunities for development and promotion.

• Attractive package of benefits.

• Work model: remote or hybrid (2 days per week from the office)

We reserve the right to contact the selected candidates.