(Senior) Machine Learning Engineer – Pricing (m/f/d)

Role overview Work at the crossroads of machine learning engineering and pricing, building and operating the systems behind a Dynamic Pricing platform. The role takes ML work beyond experimentation and into reliable production, partnering closely with Data Science, Data Infrastructure, and business stakeholders to shape the technical foundation of pricing capabilities.

Responsibilities - Take end-to-end ownership of ML models from development and integration through deployment and live monitoring. - Operationalize models in a stable, maintainable way and proactively address common pitfalls of moving from experimentation to production. - Implement training workflows in Snowflake-based environments so data and ML components work smoothly together. - Build and evolve applications and services around the Dynamic Pricing System on Snowflake, enabling ML-driven logic. - Maintain an overview of complex system landscapes, understand dependencies, and integrate ML components robustly. - Translate business and analytical requirements into technical solutions and bridge stakeholders, Data Science, and Data Infrastructure.

Requirements - Strong hands-on MLOps experience productionizing machine learning models and running them reliably. - Production-oriented Python engineering with confidence in software architecture and testing, including scikit-learn pipelines. - End-to-end ML lifecycle experience across training, feature engineering, evaluation, monitoring, drift detection, training-serving skew, and model versioning. - Hands-on work with Snowflake or comparable data platforms in ML-related contexts. - Comfort navigating complex landscapes across applications, services, data flows, and infrastructure. - Familiarity with CI/CD pipelines and Docker. - Structured, self-driven ownership and clear communication with technical and non-technical stakeholders. - Fluent professional English.

Nice to have - Pricing domain knowledge such as dynamic pricing, price optimization, or pricing experimentation.

Benefits and work setup - Remote work within Germany or hybrid from offices in Düsseldorf or Berlin. - Family-friendly working hours, generous home office policy, and ergonomic on-site workstations. - Short decision-making paths, autonomy, and an annual development budget. - Subsidies for company pension plans, mobility support, discounted fitness memberships or an in-house fitness room, and team events.