Machine Learning Research Intern (PhD)

Expedia Group; Greater London; Hybrid; GBP 45,000 - 55,000; Full time

Benefits offered by this job

Hybrid Work Policy

Travel discounts

Relocation support

Full-time offer potential after study

Job summary

Expedia Group invites talented PhD students to join its Global Summer Internship Program as a Machine Learning Science Intern in London. You will work on real ML projects, prototype models, and collaborate with data scientists, engineers, and product teams.

You will gain hands-on experience with end-to-end ML workflows, from data exploration to production-ready solutions, while benefiting from mentorship and a strong support network.

Qualifications

• Must be available to commit to the full program dates: 21st June – 27th August 2027.
• Must be graduating with a PhD degree in a technical subject between December 2027 and July 2028.
• Helpful to have theoretical understanding various machine learning topics like Regression, Naïve Bayes, Deep Learning, Gradient Boosting, Random Forests, SVMs, Neural Networks.
• Helpful to have experience with programming languages like Python, R, SQL/Hive, Java.

Responsibilities

• Design, prototype, and evaluate machine learning models under guidance of senior scientists.
• Implement clean, maintainable model training and inference code with unit testing and reproducible experiments.
• Participate in low-level system design, API design, and data modeling for ML-powered features.
• Explore, analyze, and prepare data using foundational statistical and ML techniques.
• Collaborate with peers and teams to define success metrics and iterate on ML solutions.

Skills

Python

Scala

SQL

Machine Learning

Education

PhD degree in a technical subject

Job description

Expedia Group invites talented PhD students to join its Global Summer Internship Program as a Machine Learning Science Intern in London. You will work on real ML projects, prototype models, and collaborate with data scientists, engineers, and product teams.

You will gain hands-on experience with end-to-end ML workflows, from data exploration to production-ready solutions, while benefiting from mentorship and a strong support network.