At a Glance
- Tasks: Design and develop machine learning solutions for real-world personalization challenges.
- Company: Join Expedia's innovative team focused on enhancing travel experiences through technology.
- Benefits: Enjoy travel perks, generous time off, flexible work, and career development resources.
- Other info: Collaborative environment with opportunities to influence technical direction and grow your career.
- Why this job: Make a real impact in the travel industry with cutting-edge machine learning technologies.
- Qualifications: Bachelor's degree in a technical field and 8+ years of relevant experience required.
The predicted salary is between 80000 - 100000 € per year.
The Unified Personalization Service (UPS) team is part of Expedia Product & Technology. UPS builds Expedia Group’s centralized, real‑time personalization engine across brands and channels, powering ranking, recommendations, retrieval, and other adaptive experiences that help travelers see more relevant, contextual, and useful experiences throughout their journey.
Benefits
We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, flexible work model, and career development resources to fuel employees’ passion for travel and ensure a rewarding career journey.
In this role, you will:
- Design, develop, and apply machine learning solutions to real‑world personalization, product, and business problems, translating ambiguous opportunities into scalable models, experiments, and production‑ready capabilities.
- Drive end‑to‑end scientific work across problem formulation, data exploration, feature engineering, model development, evaluation, and iteration, with strong attention to measurable impact.
- Partner closely with engineers, product, and business stakeholders to integrate machine learning solutions into services and workflows, including system design, API design, and data modeling considerations.
- Use strong technical judgment to select appropriate methods, validate outcomes, and improve model performance, reliability, and operational quality across multiple problem domains.
- Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real‑world products.
- Contribute deep technical expertise across related domains, helping raise scientific and engineering quality through experimentation, documentation, mentoring, and reusable approaches that support broader team effectiveness.
Minimum Qualifications
- Bachelor’s degree in Computer Science or a related technical field; or equivalent related professional experience.
- 8+ years of relevant professional experience.
- Demonstrated ownership of machine learning solutions at the service or multi‑service level, including problem definition, model development, evaluation, and operationalization within a product or technical domain.
- Strong foundation in machine learning methods, statistical analysis, experimentation, and data‑driven decision making, with hands‑on coding experience in scientific and production‑oriented environments.
- Experience working with cross‑functional partners to deploy technical solutions, with core expectations in scalable model development, data modeling, and integration into software systems.
Preferred Qualifications
- Advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Experience delivering machine learning solutions at scale, including architecture considerations, production monitoring, model lifecycle management, and operational excellence in live environments.
- Demonstrated ability to influence technical direction within a domain through rigorous experimentation, strong scientific reasoning, pragmatic solution design, and clear communication with cross‑functional partners.
- Strong experience with recommendation, ranking, retrieval, search, personalization, ads, marketplace, e‑commerce, or similarly complex applied ML systems.
- Experience with neural recommendation systems, sequential or session‑based recommendation, transformer‑based recommenders, semantic retrieval, generative retrieval, or representation learning at scale.
- Experience with foundation models, LLMs, embedding models, semantic IDs, hybrid LLM‑recommender systems, two‑stage retrieval and ranking systems, or retrieval‑augmented personalization workflows.
- Relevant academic publications, patents, open‑source contributions, technical blog posts, industry talks, or other contributions to the ML/recommender‑systems community.
Accommodation requests
If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability, or age.
Senior Machine Learning Scientist, Personalization employer: Expedia, Inc.
Expedia Group is an exceptional employer for Senior Machine Learning Scientists, offering a vibrant work culture that champions innovation and collaboration within the Unified Personalization Service team. With a comprehensive benefits package that includes exciting travel perks, generous time-off, and flexible work models, employees are empowered to pursue their passion for travel while enjoying ample opportunities for career development and growth in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Scientist, Personalization
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Expedia. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your machine learning expertise. When you get the chance to chat with recruiters or hiring managers, having something tangible to discuss can really set you apart.
✨Tip Number 3
Be ready for technical interviews! Brush up on your coding skills and be prepared to solve real-world problems on the spot. Practising common machine learning scenarios can help you feel more confident.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team at Expedia.
We think you need these skills to ace Senior Machine Learning Scientist, Personalization
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Scientist role. Highlight your machine learning projects, especially those related to personalization and real-world applications.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about machine learning and how your background makes you a great fit for our team. Share specific examples of your work that demonstrate your ability to drive impactful solutions.
Showcase Your Technical Skills:Don’t shy away from detailing your technical expertise in machine learning methods and tools. Mention any relevant coding experience and how you've applied these skills in previous roles to solve complex problems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity with the UPS team!
How to prepare for a job interview at Expedia, Inc.
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially those relevant to personalization. Be ready to discuss specific algorithms and their applications in real-world scenarios, as well as your hands-on experience with coding and model development.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled ambiguous problems in the past. Highlight your approach to problem formulation, data exploration, and feature engineering, and be ready to discuss the measurable impact of your solutions.
✨Collaborate Like a Pro
Since this role involves partnering with engineers and product stakeholders, think of examples where you've successfully collaborated across teams. Emphasise your communication skills and how you’ve integrated machine learning solutions into workflows.
✨Stay Current with Trends
Familiarise yourself with the latest trends in AI/ML, especially in recommendation systems and personalization. Be prepared to discuss any recent projects or research you've been involved in, and how they relate to the evolving landscape of machine learning.