Machine Learning Scientist III

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.