Berlin-based ML Platform Engineering Manager

KAYAK; Berlin (MD); Hybrid; USD 157,000 - 213,000; Full time

Benefits offered by this job

Work from almost anywhere 20 days/year

Therapy sessions via SpringHealth

HeadSpace subscription

No meeting Fridays

Paid parental leave

Paid volunteer time

Development Dollars

Leadership development

Access to on‑demand e‑learnings

Travel discounts

Office in Friedrichshain

Job summary

KAYAK, part of Booking Holdings, is seeking a Machine Learning Engineering Manager to lead the Berlin-based ML Platform team. This senior, hands-on leader will own the platform's direction, roadmap, and delivery while staying engaged with architecture and core ML challenges.

You will build self-service capabilities for training, deployment, serving, and monitoring so teams can ship production ML safely and at scale. This role requires office presence in Berlin 3 days per week.

Qualifications

• 5+ years of experience with ML lifecycle systems.
• Hands-on production ML experience with platforms or infrastructure.
• People leadership including hiring and coaching.
• Strong ownership, judgment and systems thinking.

Responsibilities

• Own the strategy and roadmap for the shared ML Platform.
• Lead Berlin-based team of ML Platform Engineers.
• Drive platform architecture and ML lifecycle direction.
• Build and evolve training orchestration, model serving, feature management, and LLM workflows.
• Champion reliability with monitoring, incident response, and production readiness.
• Define ownership boundaries between platform and downstream teams.
• Collaborate with Data Science, Engineering, and Operations on complex initiatives.

Skills

ML platform leadership

People leadership

Systems design

Production ML

Cross-functional collaboration

Tools

Python

Kubernetes

GitHub Actions

Kafka

AWS

Airflow

Trino

Job description

KAYAK, part of Booking Holdings, is seeking a Machine Learning Engineering Manager to lead the Berlin-based ML Platform team. This senior, hands-on leader will own the platform's direction, roadmap, and delivery while staying engaged with architecture and core ML challenges.

You will build self-service capabilities for training, deployment, serving, and monitoring so teams can ship production ML safely and at scale. This role requires office presence in Berlin 3 days per week.