Machine Learning Engineer Manager

Berlin · 5+ years experience · Full-time · Hybrid · Posted Oct 12, 2026

At a glance

KAYAK is seeking a Machine Learning Engineering Manager to lead the development and evolution of its shared Machine Learning Platform in a senior, hands-on technical leadership role.
You will lead a Berlin-based team building the shared infrastructure and developer workflows that take models from experimentation to reliable production.
The role involves owning the technical direction, roadmap, and delivery while staying hands-on with architecture and complex engineering problems.

Own the strategy and roadmap for KAYAK’s shared Machine Learning Platform, aligning technical investments with business needs and long-term platform evolution.
Lead, mentor, and grow a high-performing Berlin-based team of Machine Learning Platform Engineers, fostering technical excellence, autonomy, and operational accountability.
Drive technical direction across platform architecture and the ML lifecycle, contributing hands-on to high-impact problems and simplifying legacy systems where it creates clear value.
Build and evolve shared ML capabilities, including training orchestration, model serving, feature management, and LLM workflows, improving developer experience and enabling teams to deliver production-ready ML solutions efficiently.
Champion platform reliability and operational excellence, establishing robust monitoring, alerting, incident response, and production-readiness standards.
Define clear ownership boundaries so the platform team owns shared infrastructure and lifecycle tooling, while downstream teams own use-case-specific model and business logic.
Collaborate with Data Science, Engineering, and Operations teams to plan and deliver complex, multi-team initiatives, ensuring clear alignment on scope, dependencies, and timelines.

Strong technical foundations in software engineering, machine learning, and systems design, backed by significant hands-on experience building and operating production ML systems, platforms, or infrastructure.
At least 5 years of experience with ML lifecycle systems, including training orchestration, model serving, feature management, and monitoring, with a solid understanding of scalability, reliability, and operational trade-offs.
Meaningful people leadership experience, including hiring, coaching, performance management, and developing experienced technical talent, while maintaining a high technical bar and contributing hands-on where it matters most.
Strong ownership, judgment, and systems thinking, with the ability to balance platform evolution, developer experience, reliability, cost, and technical debt while influencing senior stakeholders.
Ability to lead across organizational boundaries, aligning teams around shared infrastructure, navigating competing priorities, and driving platform adoption through collaboration rather than authority.
Fluency with AI-assisted workflows, leveraging modern tools to improve productivity and quality while critically evaluating their outputs and limitations.
Curiosity, humility, and a collaborative mindset, with a commitment to continuous improvement and the ability to inspire the same in others.

Hands-on experience with technologies relevant to KAYAK’s stack, such as Python, Kubernetes, GitHub Actions, Kafka, AWS, Airflow, and Trino.
Experience building LLM or agent workflows, including prompt or dataset-processing pipelines