Machine Learning Scientist III Job Central London area,City of Westminster England UK,Software Development

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. 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. Join us and build for travelers everywhere.

Introduction

to the Team

Expedia Technology teams partner with our Product teams to create innovative products, services, and tools that deliver high-quality experiences for travelers, partners, and employees. A singular technology platform powered by data, machine learning, and AI provides secure, differentiated, and personalised experiences that build loyalty and traveler satisfaction.

In this role, you will:

Develop, evaluate, and improve machine learning models and algorithms for Content AI applications.
Design and implement end-to-end machine learning solutions, including data preparation, feature engineering, model training, validation, deployment, monitoring, and continuous optimisation.
Apply statistical analysis, experimentation, and data-driven decision-making to assess model performance and guide technical direction.
Collaborate with engineers, product managers, applied scientists, and domain experts to translate ambiguous business problems into scalable ML solutions.
Contribute to system design, low-level design, API development, and data modelling for production machine learning systems.
Build and operate production solutions using technologies such as Python, Tensor Flow, PyTorch, Redis, Airflow, Docker, Kubernetes, and cloud-native infrastructure.
Design and deploy scalable batch and real-time ML pipelines supporting customer-facing applications.
Develop and ope rationalise LLM applications, RAG systems, and Generative AI capabilities for content understanding, summarisation, classification, and recommendation use cases.
Build evaluation frameworks and observability solutions to monitor model quality, reliability, latency, drift, and business impact.
Evaluate trade-offs between model quality, scalability, latency, and infrastructure cost when developing AI-powered products.
Partner with engineering teams to deploy and scale machine learning systems in production.
Produce clear technical documentation and share expertise through mentorship, design reviews, and technical leadership.

Experience and Qualifications

Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Engineering, Data Science, or a related technical field; or Equivalent related professional experience.
5+ years of industry experience developing machine learning solutions in production environments.
Proficient programming and software engineering skills in Python, including experience building production-grade services and APIs.
Experience with machine learning frameworks such as Tensor Flow and/or PyTorch.
Experience owning machine learning solutions across the full lifecycle, including experimentation, evaluation, deployment, monitoring, and operational improvement.
Experience building and operating production ML systems at scale.
Understanding of distributed systems, data structures, algorithms, system design, low-level design, API design, and data modelling.
Experience with batch and real-time data processing systems, databases such as Redis, and low-latency serving technologies such as KServe, FastAPI.
Ability to partner effectively with cross-functional teams to deliver measurable machine learning outcomes.

Preferred qualifications

Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Data Science, or a related STEM field.
Experience applying Generative AI and LLMs to customer-facing products and designing, building, or scaling RAG systems.
Experience in search, ranking, recommendations, personalisation, content intelligence, moderation, NLP, computer vision, or related AI domains.
Experience with Airflow or comparable workflow orchestration platforms.
Experience with cloud-native environments and container technologies, including Docker and Kubernetes.
Experience…