Senior MLOps Engineer at Enpal B.V.

Berlin, , Germany -

Full Time

Start Date

Immediate

Expiry Date

29 Apr, 26

Salary

0.0

Posted On

29 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

MLOps, Machine Learning, AI Governance, Cloud Infrastructure, Container Orchestration, Python, ML Lifecycle Tooling, Snowflake, Databricks, AutoML, Data Engineering, GenAI, CI/CD, Monitoring Systems, Model Registry, Feature Store

Industry

Services for Renewable Energy

Description

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—impacting how Enpal scales ML/GenAI. Work with a modern data stack: Snowflake, Databricks, Airflow, Terraform, Azure. Join a mission-driven team committed to sustainability, innovation, and continuous learning. Our vision is to create Best Data Platform in Germany. Competitive salary, flexible working arrangements, and an empowering team culture. Ready to build the future of energy—and the infrastructure that powers AI at scale? Apply now and join us on our journey Additional Information Work in Germany's first green unicorn and actively shape the solar energy revolution. The sun shines all over the world - at Enpal you will find a highly motivated and diverse team with more than 65 different nationalities. Would you rather keep your pet company at home or your colleagues at the office? Even after the pandemic, we offer you a hybrid working model We fulfill every start-up cliché - in our modern office in Berlin-Friedrichshain, you'll find everything your heart desires, from a ping-pong table and yoga corner to a roof terrace and stocked drinks fridges. Your kick-start at Enpal - Get to know the company, your team colleagues and our founder Mario on your onboarding day. Stay up to date - Whether it's company figures at our monthly all-hands meetings or how a photovoltaic system works at the Lunch & Learn, you'll always know exactly what's going on. Energy transition only works together - At Enpal, you can expect a legendary team spirit and unforgettable team events. No mistakes, no progress - We live a strong feedback culture and grow with your input, either personally or anonymously via our feedback tool Culture Amp. At Enpal, we are proud of the diversity of our team. No decisions are made on the basis of skin colour, religion or religious belief, ethnic or national origin, nationality, gender identity, sexual orientation, disability or age, either during recruitment or employment. Enpal stands for a safe workplace and takes action against discrimination and harassment of any kind.

Responsibilities

As a Senior MLOps Engineer, you will take ownership of the machine learning platform and shape the strategy for ML/GenAI enablement. This includes ensuring compliance with regulations, designing infrastructure, and enabling teams across the company to leverage ML capabilities.