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Expedia Group

Technical Product Manager

Expedia Group
Spain · Full-time · Mid-Senior

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.


Why Join Us?


To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.


We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.


Technical Product Manager III - Machine Learning Engineering


Introduction to team


Private Label Solutions (PLS) is the B2B arm of Expedia Group. We open up our supply and innovative technology to businesses looking to take on the world of travel. These businesses, sometimes referred to as our ‘demand partners’, include global financial institutions (e.g. AMEX), corporate managed travel, offline travel agents (e.g. Flight Centre), global travel suppliers (e.g. Delta) and many more.


In this role, you will:


  • Collaborate closely with the ML Engineering team to manage and prioritize the product backlog
  • Translate business requirements into technical specifications for ML infrastructure and data pipeline projects
  • Coordinate cross-functional efforts to streamline the model development to production pipeline
  • Manage project timelines, milestones, and deliverables for ML infrastructure initiatives
  • Facilitate communication between technical teams and business stakeholders
  • Create and maintain product roadmaps for ML infrastructure and MLOps capabilities
  • Gather and analyze user feedback to inform product improvements and new feature development
  • Collaborate with ML scientists and engineers to define KPIs and success metrics for ML systems
  • Support the implementation of best practices for MLOps and CI/CD pipelines for ML model deployment
  • Assist in resource planning and allocation for ML engineering projects
  • Stay informed about industry trends in ML infrastructure and engineering practices to inform product strategy


Experience and qualifications


  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
  • 5+ years of experience in technical product management, preferably in ML or data-intensive domains
  • Strong understanding of ML concepts, infrastructure, and engineering practices
  • Experience with Agile methodologies and project management tools (e.g., Jira, Confluence)
  • Familiarity with cloud platforms (AWS, GCP) and containerization technologies (Docker, Kubernetes)
  • Understanding of data systems (e.g., Spark, Kafka, Airflow, Data Lakes) and ML model serving technologies
  • Experience in creating technical specifications and product requirements documents
  • Proven track record of delivering complex technical products or infrastructure projects
  • Strong communication skills and ability to bridge technical and non-technical stakeholders
  • Ability to prioritize and manage multiple projects simultaneously in a fast-paced environment
  • Experience in conducting stakeholder interviews and gathering user requirements
  • Passion for ML and data technologies and their business applications
  • Demonstrated ability to translate business needs into technical solutions and drive strategic alignment.

Key Skills

Ranked by relevance

mlops containerization machine learning product manager docker kafka cloud spark cicd jira aws gcp
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Posted
Aug 08, 2025
Type
Full-time
Level
Mid-Senior
Location
Madrid

Industries

Software Development Travel Arrangements Internet Marketplace Platforms

Categories

Product Management Marketing

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