Machine Learning Engineer

Expedia Group
London
1 day ago
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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.

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