Senior ML Ops Engineer

About KAYAK

KAYAK, a part of Booking Holdings, is a premier travel search engine handling billions of queries to assist users in finding flights, accommodations, rental cars, and vacation packages. Alongside its suite of global metasearch brands including momondo, Cheapflights, and HotelsCombined, KAYAK prides itself on innovation and aims to simplify travel planning for everyone.

Role Overview

We are seeking a Senior Machine Learning Operations (MLOps) Engineer to design and implement infrastructure that supports the lifecycle of machine learning models from experimentation to production. This leadership-level, hands-on position bridges data science and production engineering, ensuring ML models are reliable, scalable, and performant.

Key Responsibilities

• Develop and maintain end-to-end machine learning infrastructure, including CI/CD pipelines, model orchestration, and automated training workflows that scale without requiring manual intervention.
• Manage the deployment and serving of machine learning models, establishing standards and tools to guarantee low latency and high availability.
• Build core MLOps systems such as feature stores, model registries, and automated monitoring frameworks for performance and data drift.
• Collaborate with Operations to enable Kubernetes autoscaling and GPU provisioning, facilitating accessible, self-service tools for ML practitioners, including managing Kubernetes-based development clusters.
• Enhance platform reliability through resilient monitoring using observability tools; define service-level objectives and implement automation to minimize manual tasks and improve uptime.
• Empower data scientists with streamlined, standardized workflows ("golden paths") that optimize the model development lifecycle.

Required Qualifications

• Proven experience building and running ML platforms in production.
• Strong working knowledge of containerization (Docker), orchestration (Kubernetes), Linux internals, and scalable model serving.
• Familiarity with ML lifecycle tools including orchestration frameworks, feature stores, model registries, and monitoring systems for drift and performance.
• Experience managing production systems encompassing SLO definitions, observability (e.g., Prometheus, Grafana, Datadog), incident response, and failure diagnostics, with a focus on automation.
• Ability to produce production-grade code in Python or similar languages.
• Experience updating production infrastructure prioritizing reliability, risk mitigation, and cost-efficiency while ensuring continuity.
• Strong ownership of technical results, data-driven decision-making, and effective communication skills for diverse audiences.

Benefits and Perks

• Ability to work remotely up to 20 days per year.
• Mental health support through company-paid therapy sessions (SpringHealth) and HeadSpace subscriptions.
• Annual company-wide week off for full team rejuvenation.
• No meetings on Fridays.
• Paid parental leave and paid volunteer time.
• Career development opportunities including development funds, leadership training, and access to extensive e-learning resources.
• Employee travel discounts and active resource groups.
• Generous vacation policy: 6 weeks paid leave plus birthday off.
• Free lunch twice weekly.
• Contributions to pension plans, subsidies for public transportation, and bike leasing programs.
• Regular social events, including monthly gatherings, happy hours, and sports teams.
• Modern office located in Friedrichshain, Berlin.

Inclusion

KAYAK fosters an inclusive environment where all individuals can thrive and contribute meaningfully. Adjustments for interviews, applications, or on-the-job needs are welcomed to ensure equitable opportunity.

Working Hours

This position requires onsite presence in the Berlin office at least three days per week.