Machine Learning Ops

Do you love building the engineering backbone that turns machine learning models into products used by millions? As a Senior MLOps Engineer, you'll work at the intersection of data science, engineering, and DevOps to build the APIs, infrastructure, and optimisation work that take pricing and demand models from notebooks to production. Your work will directly shape products used by millions of consumers across Europe.

What You'll Do:

• Take Models to Production: Deploy pricing and demand models into production, building and maintaining the APIs and serving infrastructure that make them reliable at scale.
• Own the Engineering Backbone: Be the bridge between Data Scientists and production systems — turning experimental POCs into robust, maintainable Python applications.
• Build & Operate Infrastructure: Set up and maintain the environments, CI/CD pipelines, and cloud infrastructure the team depends on day-to-day.
• Make Data Usable for ML: Work on optimisation projects and ensure data quality, consistency, and documentation across production models and datasets.
• Drive Operational Excellence: Implement monitoring, automated testing, and observability so production systems stay healthy and issues get caught early.
• Partner Across Teams: Collaborate closely with Data Scientists, Analysts, and Engineers to turn prototypes into production-ready solutions that actually ship.

The Team:

You'll join a newly formed Dynamic Pricing & Revenue Management team, working alongside a Data Scientist and a Data Analyst towards one core goal: building a smart, dynamic, data-driven pricing engine that directly drives commercial outcomes. The team values ownership, collaboration, and pragmatic problem-solving — and makes heavy use of modern AI tooling (Claude, Copilot, Codex) to move faster. You'll work with a modern stack (Airflow, dbt, Redshift, MLflow, SageMaker, Terraform, AWS EKS) and teammates who care deeply about impact.

What They're Looking For:

• 4+ years of experience in Software Engineering, MLOps, DataOps, or DevOps — ideally with engineering projects related to data and ML
• Strong hands-on Python skills — you write clean, production-quality code
• Experience building and deploying APIs and services in production
• Solid grounding in CI/CD, Docker, and infrastructure-as-code (e.g. Terraform)
• Familiarity with cloud platforms (AWS preferred)
• Exposure to ML model deployment (MLflow, SageMaker, or similar) is a strong plus
• Desire to use cutting-edge LLM tools and agents to boost your own and the team's productivity

What They Offer:

• Competitive salary and hybrid working setup with 50% in-office time in Munich
• Personal learning budget with a strong focus on AI + mentorship from outstanding colleagues
• Up to 8 weeks per year working remotely from other inspiring locations
• Gym discounts
• Bonus, pension, private healthcare
• The chance to join one of Europe's fastest-growing consumer tech scale-ups — 700+ colleagues from 60+ nations, millions of users, and a proven business model backing a team that still moves like a startup