Principal Machine Learning Engineer (Mobile Gaming)

TL;DR

Principal Machine Learning Engineer (ML/Python): Designing and deploying production-ready ML systems for high-performing mobile gaming products with an accent on the full ML lifecycle and scalable infrastructure. Focus on translating ambiguous business problems into structured ML solutions and establishing foundational ML best practices.

Location: Hybrid in Hamburg, Germany (Office: Tue-Thu, Remote: Mon & Fri)

Company

A high-growth company building top-ranking consumer mobile gaming products.

What you will do

• Design, build, and deploy production-ready ML models that directly influence product performance, user behavior, and revenue.
• Own the end-to-end ML lifecycle, from experimentation and validation to production deployment and continuous monitoring.
• Collaborate with Data Scientists and Analysts to translate metrics and hypotheses into scalable ML solutions.
• Partner with Data Engineers to ensure robust data pipelines, feature availability, and reliable model deployment.
• Define the company's ML foundations, establishing best practices, tooling, and architecture for versioning and monitoring.
• Translate ambiguous business problems into structured ML systems, making technical trade-offs to bring clarity.

Requirements

• 7+ years of solid experience in machine learning, applied statistics, or data science with a focus on production use cases.
• High proficiency in Python and experience with modern ML libraries such as TensorFlow or PyTorch.
• Experience with SQL, data warehouses, ETL/ELT workflows, and Databricks.
• Hands-on experience with deploying, versioning, and monitoring models in real-world environments.
• Ability to leverage AI tools (specifically Claude) and LLM APIs to accelerate prototyping and production development.
• Must be based in or able to work in a hybrid model in Hamburg, Germany.

Culture & Benefits

• Driven, entrepreneurial environment with high individual ownership.
• Opportunity to work on apps that rank in the top 5 of their categories.
• Transport subsidy and a dedicated learning budget.
• Wellness and gym perks, including workation options.
• Bi-weekly team lunches.