Your Role
As our Senior MLOps Engineer, you will take ownership of our machine learning platform and help shape Enpal鈥檚 strategy for ML/GenAI enablement, from technical infrastructure to regulatory compliance.
AI Governance & Legal Responsibility
- Act as AI Act Steward within Enpal - ensure compliance with the EU AI Act and future regulations.
- Build and maintain a central registry of all ML and GenAI use cases and models.
- Design processes to monitor high-risk models, ensuring explainability, robustness, and fairness.
MLOps Infrastructure
- 路 Design and implement core infrastructure, including:
- A centralized Model Registry
- A scalable Feature Store
- Automated Monitoring systems for both ML and GenAI models
- Orchestration pipelines for retraining and redeployment (e.g. Airflow-based)
- 路 Collaborate with Data Engineering to ensure seamless CI/CD for ML workflows.
GenAI & Agentic Use Cases
- Drive implementation of GenAI-based agents that interface with our DWH (e.g. access distribution, text-to-SQL, semantic search, natural language querying).
- Prototype and deploy agentic LLM workflows using Snowflake and other enterprise data assets.
Central Data Science Enablement
- Provide ML-as-a-Service capabilities to empower teams across the company.
- Be the go-to person for evaluating and enabling ML/GenAI PoCs with business units.
- Champion the use of AutoML and build reusable tools for scalable experimentation.
- Proactively identify and implement high-impact use cases, leveraging data across the company.