Machine Learning Engineer

Expedia Group
London
1 month ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer - Bristol

Audio Machine Learning Engineer

Machine Learning Engineer III – Advertising Tech


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, when one of us wins, we all win.

We provide a full benefits package—including exciting travel perks, generous time-off, parental leave, flexible work, and leading career development—to fuel your passion for travel and support your career journey. We’re building a more open world. Join us.


About the Role:


Our Advertising Engineering team powers the decisioning, delivery, and personalisation of billions of ad impressions each year across Expedia Group’s 200+ global brands. As a Machine Learning Engineer III, you will harness terabytes of traveler, campaign, and context data to build ML systems for:


  • Real-time ad selection, dynamic creative optimisation, and campaign effectiveness
  • User targeting and bidding (e.g. bid optimisation, click/conversion prediction, contextual relevance)
  • Personalisation at global scale, with a measurable impact on advertisers and travelers alike


Who Should Apply?


If you have hands-on experience building ML models and pipelines in advertising technology environments, such as with a Demand-Side Platform (DSP), Supply-Side Platform (SSP), Ad Exchange, ad server, or a large digital consumer platform’s advertising team—this is a chance to drive innovation and business impact at the heart of Expedia’s global advertising business. You’ll work shoulder-to-shoulder with scientists and engineers from ad tech giants, owning production systems with reach and complexity on par with the world’s leading AdTech firms.


What You Will Do:


  • Design and scale ML pipelines for programmatic ad selection, campaign performance, and audience segmentation
  • Deploy Spark-based, distributed, and real-time data flows for bidding, targeting and ad performance optimisation
  • Partner with Ads Data Scientists and Software Engineers to bring models from experimentation into global production (AWS, Kubernetes, Databricks)
  • Deliver advanced ML APIs and services, enabling ad delivery, targeting, and creative personalisation across Expedia Group
  • Apply best practices in MLOps, model reliability, explainability and monitoring for high-stakes, high-scale ad delivery
  • Mentor junior engineers and lead architectural discussions
  • Continuously explore, recommend, and implement new ML methods and AdTech approaches


Required Experience:


  • 5+ years as a Machine Learning Engineer, Data Scientist, or Applied Scientist, with 2+ years in advertising/ad tech
  • Deep expertise in Python and either Scala or Java; strong Spark/distributed computing background
  • ML production experience (PyTorch, TensorFlow), specifically for AdTech (e.g., CTR/CVR prediction, ranking, targeting, bidding, or user modelling)
  • Cloud-native workflows (AWS, EMR, Databricks, SageMaker, Kubernetes); orchestration tools (Airflow, etc.)
  • Experience integrating ML with business-critical ad systems and optimising for campaign/ad KPIs


Preferred:


  • Experience with real-time ad systems (streaming, low-latency models)
  • Prior work at Ad Platforms (DSP/SSP/Exchange/Network) or digital teams building ad personalisation, targeting, or optimisation
  • Travel, e-commerce, or publisher/platform ad tech experience
  • Hands-on with large-scale GPU/distributed training

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.