Machine Learning Scientist III

UK - London, United Kingdom

Expedia Group

Let’s transform travel together.

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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.

Machine Learning Scientist III

Introduction to team

Private Label Solutions (PLS) is the B2B arm of Expedia Group. We bring Expedia Group's innovative technology and distribution solutions to partners across the world. These businesses include global financial institutions, corporate managed travel, offline travel agents, global travel suppliers (like major airlines) and many more..

We are looking for a ML Scientist III to join the Private Label Solutions (PLS) Machine Learning Science team supporting the business-to-business (B2B) arm of Expedia Group (EG). You will join a team that builds end-to-end ML solutions for ranking problems, recommendation engines as well as optimizing our pricing and commission offerings contributing substantial value for our partners and for EG. We embrace test and learn by continuously experimenting, analyzing and improving our algorithms which has helped the B2B business become one of the fastest growing at Expedia Group.

We’re looking for a passionate and experienced applied scientist to join our team at Expedia Group. This is a high-impact individual contributor role where you will own and lead machine learning solutions end-to-end — from problem definition and experimentation to deployment and monitoring in production.
This is a true applied science role. You can expect to spend half of your time on ML engineering tasks, such as building data processes, implementing feature engineering, deploying models at scale, monitoring the impact of ML production systems and understanding the interactions of your models with the rest of the EG stack. The other half will be focused on research, experimentation, and model development. We’re seeking someone who thrives in fast-paced environments, adapts quickly to shifting priorities, and is motivated by real-world impact.

In this role, you will

  • Lead and own entire ML projects end-to-end, including ideation, data exploration, modelling, deployment, and monitoring.

  • Design and implement robust ML engineering systems, including pipelines, features, and monitoring.

  • Collaborate cross-functionally with product, engineering, and analytics to ensure your solutions are scalable, performant, and aligned with business goals.

  • Seed ideas, drive technical direction, and deliver hands-on contributions throughout the project lifecycle.

  • Mentor other ML scientists and engineers, offering guidance and technical feedback to foster team development.

  • Drive continuous improvement across our ML infrastructure and workflows.

  • Clearly communicate technical concepts and solution approaches to a broad audience, including stakeholders without technical backgrounds.

Experience and qualifications:

  • Proven track record of delivering end-to-end ML solutions in a production setting both batch and real time live inference

  • Fluent in Python and PySpark, with strong experience in ML libraries such as Keras, or TensorFlow. Experience with Scala is a plus.

  • Deep understanding of the ML development lifecycle, including deployment and operationalisation.

  • Strong foundation with hands-on experience in ML engineering

  • You’re curious, driven, and collaborative – energised by new ideas and passionate about shipping impactful work.

  • Excellent communication skills, with the ability to distill and explain complex ideas to technical and non-technical audiences.

  • Committed to mentoring others and contributing to a supportive and inclusive team environment.

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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.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.

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.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Engineering Feature engineering Keras Machine Learning ML infrastructure ML models Pipelines PySpark Python Research Scala TensorFlow

Perks/benefits: Career development Flex vacation Health care Parental leave

Region: Europe
Country: United Kingdom

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