Senior MLOps Engineer (f/m/x)

Company Description

Our goal is a solar power system on every roof, a storage unit in every house, and an e-car in every garage. How are we achieving this? Enpal makes solar easy: we rent out solar power systems, electricity storage and wallboxes at an all-inclusive rate, supplemented by a low-cost green electricity tariff, and intelligently networked into an integrated overall solution.

We are just at the beginning of our journey to becoming Europe's largest energy company. That's why we're looking for talented people to accompany us on this journey, leave their footprint and celebrate successes together with us. At Enpal, you will find a dynamic working environment as well as the space to develop yourself personally and professionally and to use your strengths effectively.

As the first green unicorn in Germany and the fastest-growing energy company in Europe (FT1000 Ranking 2022 by Financial Times & Statista), we continue to advance our mission of green energy for everyone. Be part of this success story and change the world with us!

Job Description

Your Role

As our Senior MLOps Engineer, you will take ownership of our machine learning platform and help shape Enpal’s 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

• · 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)
• · 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.

Qualifications

Your Profile

Must-Haves

• 4+ years of experience in MLOps, ML engineering, or applied machine learning in production environments.
• Strong ownership mentality—you care about impact, not just implementation.
• Clear communicator who can explain complex ML concepts to non-technical stakeholders.
• Solid experience with cloud infrastructure (Azure preferred), container orchestration (Docker/Kubernetes), and IaC (Terraform).
• Proven track record with ML lifecycle tooling—model versioning, monitoring, retraining, CI/CD.
• Familiarity with MLFlow, Airflow, or similar platforms.
• Strong programming skills in Python and experience with ML frameworks
• Hands-on experience with Snowflake, Databricks, or modern data stack tools.

Nice-to-Haves

· Exposure to GenAI applications (e.g., LLM orchestration, LangChain, RAG pipelines).

· Experience interpreting and operationalizing AI regulatory frameworks, especially the EU AI Act.

· Prior experience enabling AutoML adoption or building self-serve ML platforms.

· Enthusiasm for working at the intersection of Data Engineering, AI innovation, and legal compliance.

· Collaborative and pragmatic - able to work cross-functionally across Data, Engineering, and Legal teams.

· Curious and proactive - you keep up with the latest in GenAI and MLOps, and enjoy trying new ideas.

Why Join Us?

• Help build responsible AI infrastructure from the ground up—impactin