Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Scientist III

Expedia Group
City of London
21 hours ago
Create job alert

3 days ago Be among the first 25 applicants


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 everybody knows 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.


Introduction to the team

We are seeking a skilled Machine Learning Scientist III to join Expedia Group B2B. As a global leader in B2B travel technology, PLS serves thousands of partners across diverse markets and travel segments. Recommender systems and relevance algorithms are foundational capabilities that have a significant impact on the business and are critical to the success of our partners, suppliers and Expedia Group. This applied science role will contribute to developing and implementing ML solutions for personalized recommendations, learning to rank, and relevance optimization. The ideal candidate will possess strong technical skills and commercial awareness to drive value for PLS and our partners.


In This Role, You Will

  • Own the design and implementation of end‑to‑end ML solutions for recommendations & relevance at scale that can handle high‑throughput, low‑latency personalized recommendations across diverse partner segments
  • Collaborate with senior team members and cross‑functional teams to align ML solution design with business strategy and partner needs
  • Be an integral part of a full stack team of Machine Learning Scientists and Machine Learning Engineers, contributing to technical implementation, conduct analyses and present findings to both technical and business stakeholders, translating ML concepts into actionable insights
  • Work with operations, analytics and internal product & technology teams to ensure models in production are driving expected business value and operate efficiently
  • Stay informed about relevant advancements in recommender systems and relevance algorithms through ongoing research and learning
  • Coach and mentor other scientists and engineers within the recommendations domain

Experience and Qualifications

  • You hold a PhD (preferred) or master’s degree in computer science, machine learning, mathematics/statistics, or another related field of science, with a minimum of 3+ years of industry experience in applied machine learning, including deploying recommender systems and relevance models to production.
  • You have solid knowledge of machine learning algorithms, particularly those used in recommender systems and learning to rank, as well as knowledge of statistics and A/B testing.
  • You demonstrate good communication and interpersonal skills, with the ability to work effectively in a team environment and contribute to technical discussions.
  • You show interest in staying current with the latest ML research and applying techniques to solve real‑world problems in recommendation and relevance.
  • You are proficient in programming languages such as Python, and have experience with ML frameworks like TensorFlow, PyTorch, and scikit‑learn.
  • You are familiar with cloud platforms (e.g., AWS), big data technologies (e.g., Spark), and technologies used to deploy models to production (e.g., Docker).

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.


Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Other


Industry

Software Development


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Scientist III - Rankings & Personalization

Machine Learning Scientist III

Machine Learning Scientist III – Experimentation Science (Statistical Methodologies)

Machine Learning Scientist III

Machine Learning Specialist

Machine Learning Researcher

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.