Machine Learning Engineer

Expedia Group
City of London
4 days ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer III


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.


Expedia Group’s Advertising Engineering team is dedicated to building innovative solutions that empower travel advertisers to connect with millions of travelers worldwide. Our platform enables brands to leverage Expedia’s global network of leading travel brands and sites, offering a diverse portfolio of advertising and sponsorship opportunities. With over 200 branded sites in 75 countries and 35 languages, we help advertisers reach 112 million monthly unique visitors.


As a Machine Learning Engineer III on this team, you will design and implement scalable machine learning systems that optimise ad selection, campaign performance, and creative personalisation at a global scale. You will work in a highly collaborative environment with ML scientists and software engineers to deliver impactful solutions for the advertising domain.


In this role, you will:


  • Design, implement, and maintain large-scale machine learning pipelines for advertising use cases, including feature engineering, model training, validation, and deployment.
  • Build real-time and batch data processing systems to support ad targeting, campaign optimisation, and experimentation.
  • Collaborate with ML scientists and software engineers to integrate ML models into production systems and deliver measurable business impact.
  • Develop APIs and services that enable ML-driven advertising solutions across Expedia Group’s global platform.
  • Optimize Spark-based applications for large-scale data processing and ensure system reliability and performance.
  • Implement strategies for training models on massive datasets using distributed computing and GPU acceleration.
  • Contribute to design discussions and code reviews, ensuring best practices in ML engineering and software development.
  • Mentor junior engineers and share knowledge within the team and broader engineering community.
  • Continuously explore new technologies and methodologies to improve ML systems and advertising solutions.
  • Participate in a community of practice to share and gain knowledge across the organization.


Required qualifications:


  • Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
  • 5+ years of professional experience with a Bachelor’s degree OR 3+ years with a Master’s degree.
  • Proven experience building and deploying ML pipelines in production environments.
  • Strong programming skills in Python and at least one other language (e.g., Scala or Java).
  • Expertise in Spark and distributed data processing frameworks.
  • Proficiency with ML libraries such as PyTorch and TensorFlow.
  • Experience with cloud platforms (AWS, EMR, Kubernetes, Docker) and ML platforms (Databricks, SageMaker).
  • Familiarity with workflow management tools (e.g., Airflow).
  • Strong understanding of software design principles, data structures, and design patterns.
  • Ability to debug, test, and monitor complex systems effectively.


Preferred: qualifications:


  • Experience with real-time applications and streaming architectures.
  • Knowledge of advertising technology, e-commerce, or travel industry.
  • Hands-on experience with large-scale model training and optimization using GPUs or distributed systems.

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.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.