Expedia

The application is paired with an immersive strength-based online assessment and a skills-based assessment, and candidates who progress sit two virtual interviews covering specialized and behavioral skills. The interview guide notes that for some roles those interviews include a technical assessment, business case, or work sample, and that behavioral questions follow the STAR (Situation, Task, Action, Result) format. The strength assessment sits in front of the skills test, so a candidate who walks in expecting only a coding screen misses the round that gates progression to the team interviews.

Expedia Group publishes four named emerging-talent tracks, each drawing from firm-listed function streams (Commercial, Data Science/Analytics, Finance, Machine Learning Science, Marketing, Product Management, Program Management, Software Engineering, User Experience, Design):

• Internship: 8 to 14 weeks, starting May or June, in Montreal, Bangalore, Gurgaon, London, Austin, Chicago, and Seattle.
• Graduate: 12 to 24 months, starting January or August by location, in the same seven cities.
• Apprenticeship: 12 to 18 months, starting spring or fall, in London, Chicago, and Seattle, with 80% of time on a technical team and 20% with an external training provider.
• Military Placement: 12 weeks, starting January or September, in the UK and the USA.

The four tracks open more than one entry point for the same candidate profile. A UK software-engineering graduate, for example, has both the graduate scheme and the apprenticeship as live options in the same year, with separate fits and separate decision timelines.

A few specific points stand out from Expedia Group's own story and emerging-talent materials:

• A multi-brand consumer portfolio under one engineering organization: Expedia, Hotels.com, Vrbo, Hotwire, Orbitz, Travelocity, Wotif, and Trivago all sit inside the same group.
• Four parallel early-career tracks (Internship, Graduate, Apprenticeship, Military Placement) rather than only summer plus graduate, including a Military Placement program uncommon among the firm's tech-employer peer set.
• The apprenticeship's 80/20 split (80% on a technical team, 20% with an external training provider) is a work-study structure, not rotational shadowing.
• Machine Learning Science is a named early-career function track, distinct from generic data science.

For an applicant weighing this firm against single-brand tech employers, the practical question is whether the multi-brand surface area is a more interesting product environment than a single-brand stack of similar scale.