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Reads like a Data Leadership role: running a data team.
Berlin Office · Berlin, Germany
Live, first seen by us 22 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Cost Centers › Technology › DataFrom the employer’s posting
Own the strategy and roadmap for the shared ML Platform
Lead, mentor, and grow the Berlin platform engineering team
Build self-service training, serving, feature, and LLM capabilities
Set reliability, monitoring, and incident response standards
Coordinate multi-team initiatives with Data Science and Engineering
Own the strategy and roadmap for KAYAK’s shared Machine Learning Platform
Lead, mentor, and grow a high-performing Berlin-based team of Machine Learning Platform Engineers
Build and evolve shared ML capabilities, including training orchestration, model serving, feature management, and LLM workflows
establishing robust monitoring, alerting, incident response, and production-readiness standards
Collaborate with Data Science, Engineering, and Operations teams to plan and deliver complex, multi-team initiatives
From the employer’s posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 22
Similar jobs usually come down between day 7 and day 53.
From 7,871 similar postings that came down. Coming down is not always a hire.
10 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Bonus qualifications - 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
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
KAYAK, part of Booking Holdings (NASDAQ: BKNG), is the world's leading travel search engine. With billions of queries across our platforms, we help people find their perfect flight, stay, rental car and vacation package. We're also transforming business travel with a new corporate travel solution, KAYAK for Business.
As an employee of KAYAK, you will be part of a travel company that operates a portfolio of global metasearch brands including momondo, Cheapflights and HotelsCombined, among others. From start-up to industry leader, innovation is at our core and every employee has an opportunity to make their mark. Our focus is on building the best travel search engine to make it easier for everyone to experience the world.
KAYAK is seeking a Machine Learning Engineering Manager to lead the development and evolution of its shared Machine Learning Platform. This is a senior, hands-on technical leadership role.
You’ll lead a Berlin-based team which builds the shared infrastructure and developer workflows that take models from experimentation to reliable production. You’ll own its technical direction, roadmap, and delivery while staying hands-on with architecture and the hardest engineering problems. In partnership with the team, you’ll build self-service capabilities for training, deployment, serving, and monitoring so KAYAK teams can ship models safely and at scale.
If you’re excited to combine people leadership with building the systems that make machine learning work in production, we’d love to hear from you.
This role will be required to work from our Berlin office 3 days per week.
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
Work from (almost) anywhere for up to 20 days per year
Focus on mental health and well-being:
Company-paid therapy sessions through SpringHealth
Company-paid subscription to HeadSpace
Company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
No meeting Fridays
Paid parental leave
Paid volunteer time
Focus on your career growth:
Development Dollars
Leadership development
Access to thousands of on-demand e-learnings
Travel Discounts
Employee Resource Groups
6 weeks paid vacation + a day off for your birthday
Free lunch 2 days per week
Pension plan contributions
Public transportation subsidies
Bike leasing program
Monthly social events, Thursday happy hours, sports teams
An awesome office in Friedrichshain, Berlin
At KAYAK, we want everyone to have the space to grow, share ideas and do great work. That’s why we’re focused on hiring the best talent from all walks of life and experiences, supporting them well and making sure no one feels like they have to fit a mold to belong here.
Need any adjustments for the interview, application or on the job? No problem - just give us a heads-up. We’ve got you.
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Berlin, Germany
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