Machine Learning Engineer (Marketing)

TL;DR

Machine Learning Engineer (Marketing): Developing and maintaining large-scale production experimentation platforms and measurement tools for global travel brands with an accent on scalable system architecture and ML model integration. Focus on transforming research prototypes into robust production-ready code, optimizing testing frameworks, and building reusable data processing pipelines.

Location: Must be based in London, United Kingdom (Hybrid work model).

Company

hirify.global is a global leader in travel technology, powering brands such as Expedia, Hotels.com, and Vrbo to make travel more accessible and memorable.

What you will do

• Maintain and optimize production experimentation platform performance for 300+ annual tests.
• Build scalable data pipelines for high-volume experiment execution and analysis.
• Develop reusable code libraries and measurement tools for marketing analytics.
• Transform complex research prototypes into production-ready software solutions.
• Collaborate with cross-functional data science and engineering teams to deploy tools.
• Troubleshoot system issues and enhance logging to ensure operational reliability.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related technical field.
• Proficiency in Python, SQL, and PySpark for large-scale data processing.
• Experience building scalable systems with integrated ML/AI components in production.
• Strong understanding of system internals including memory management, caching, and distributed computing.
• Knowledge of automated testing, version control, and deployment pipelines.
• Foundational understanding of machine learning principles and statistical methods.

Nice to have

• Familiarity with cloud platforms such as AWS or GCP.
• Experience with open-source development practices.
• Knowledge of A/B testing methodologies and experimental design.

Culture & Benefits

• Comprehensive benefits package including travel perks and generous time-off.
• Flexible work model with office presence.
• Focus on career development and internal growth resources.
• Inclusive, diverse, and vibrant team culture.
• Supportive environment with focus on work-life balance.