Job Description About the team Our in-house ML team leverages applied science and advanced technology to help customers discover travel options and create unforgettable travel experiences. Here are some challenges we're tackling: Personalisation at Scale – How do we ensure that each of our millions of users has a personalised customer journey that reflects their unique preferences? Real-time Recommendations – Implementing strategies to provide instantaneous suggestions as users interact with our platform and product lines (hotels, tours, cruises, flights, experiences etc). Customer Retention – When should we proactively engage with our users, how frequently, and what incentives and channels are most effective? Revenue Management – How should we adjust product pricing and availability, considering both demand and loyalty programs? Scalable ML Infrastructure – Adopting MLOps tools and practices to support our expanding suite of models and handle a massive influx of data. About the role As a Machine Learning Engineer, you will play a key role in developing and implementing cutting-edge ML solutions to solve complex business problems. You will collaborate with cross-functional teams to design, build, and deploy models, contributing to the advancement of our technology and driving innovation. At Luxury Escapes, we embrace a start up mindset, moving fast, driving continuous improvements, while maintaining the highest standards of code quality. You will have a strong bias for action and as you uncover opportunities you will be able to present them to the team and help steer the direction of ML initiatives. Responsibilities include Develop recommendation and search systems to help customers discover great offers for their next holiday Design revenue management and customer retention solutions to optimize business operations and drive profitability Build ML models using state-of-the-art methods, from research prototyping to production deployment Work closely with your ML Engineer peers, Data Engineers, Software Engineers, and Product Managers Produce well-tested, well-documented, high-quality, easily maintainable code Implement robust model evaluation frameworks to ensure performance metrics meet business objectives Translate business needs into scientific problems to unlock tangible value Clearly communicate complex technical concepts and findings to non-technical stakeholders
