Machine Learning Scientist

Salary: £70,000 - 110,000 per year

Requirements:

• Bachelors degree in Computer Science or a related technical field, or equivalent related professional experience.
• 2+ years of relevant professional experience.
• Proven ability to own ML solutions for a well-defined service or product area, including data exploration, model development, offline and online evaluation, and partnering with engineering for integration.
• Proficiency in at least one major programming language used for ML, such as Python, and common ML/AI frameworks and tooling for model development, training, and evaluation.
• Solid grounding in core ML concepts, including supervised and unsupervised learning, model generalization, overfitting, and evaluation metrics, with experience working with real-world, noisy datasets.
• Advanced degree (Masters or PhD) in a quantitative field with a focus on machine learning, statistics, or AI, with experience applying research ideas to practical, large-scale problems.
• Experience designing and operating ML systems at scale, including feature pipelines, model training workflows, and online inference, with attention to latency, reliability, and cost.
• Demonstrated track record of leading the end-to-end lifecycle of ML solutions within a product or domain, from ideation and prototyping through experimentation, launch, and ongoing optimization.
• Strong background in experimentation and data-driven decision making, including designing robust A/B tests, interpreting results, and translating findings into product and model changes.
• Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with at least one of recommendation systems, ranking, search, personalization, forecasting, or optimization models.

Responsibilities:

• Develop, implement, and optimize machine learning models that power data-driven features and products, from problem framing through production deployment and iteration.
• Design and evaluate experiments, offline evaluations, and A/B tests to measure model impact, using statistical rigor to compare alternatives and drive decisions.
• Collaborate with engineers, product managers, and analysts to translate ambiguous business problems into well-scoped ML solutions, including data requirements, modeling approach, and success metrics.
• Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models are robust, explainable, and performant at scale.
• Safely integrate and operate AI/ML-enabled solutions that improve outcomes, including monitoring model performance, detecting degradation, and driving continuous improvements in production.
• Demonstrate familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products, contributing reusable methodologies and best practices that can be leveraged across teams and problem spaces.

Technologies:

• AI
• Support
• Machine Learning
• Model Training
• Network
• Python

More:

At Expedia Group, we help travelers explore the world, one journey at a time. We are a global travel company powered by passionate people, trusted partnerships, and leading technology, connecting travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. Our five Behaviors—Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together—help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Our Expedia Product & Technology division builds innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. This Machine Learning Scientist II role sits on the Lodging Search Ranking AI team within Expedia Product & Technology, where we develop and optimize ranking models using state-of-the-art machine learning and genAI techniques to power lodging search and personalized lodging ranking and recommendations across our portfolio. Our work directly impacts millions of travelers and travel partners each year, with results measured objectively through A/B testing. We are based in the UK, London, and this is a full-time role.

last updated 35 week of 2026