Senior Machine Learning Engineer at Bumble developing scalable AI systems for personalized user interactions. Leading machine learning model development and deployment from exploration to production.
About the role
- Machine Learning Science Graduate developing innovative ML models and techniques at Expedia Group for enhancing global travel experiences. Engaging in hands-on data science applications and collaboration with partners.
Responsibilities
- Apply statistics methods like confidence intervals, point estimates and sample size estimates to make sound and confident inferences on data and A/B tests
- Apply Natural Language models to Google keyword analysis and applying meta models to our multi-objective ranking problem
- Communicate complex analytical topics in a clean & simple way to multiple partners and senior leadership
- Conduct feature engineering and modifying existing models/techniques to suit business needs
- Develop domain expertise in fraud & risk to understand how to detect risky transactions
- Model rich and complex online travel data to understand, predict and optimize business metrics to help improve the traveler experience
- Frame business problems as data science problems with a concrete set of tasks
Requirements
- Must be available to start on August 17, 2026
- Must be graduating between December 2025 and July 2026 with a Masters degree in a technical or analytical-related subject such as Computer Science, Mathematics, Physics, Statistics, Operations Research, Electrical & Computer Engineering
- Must be willing to relocate to the city of job location if outside commuting distance
- Helpful to understand ML techniques like Regression, Naïve Bayes, Gradient Boosting, Random Forests, SVMs, Neural Networks, and NLP
- Helpful to have experience with programming, statistical, and querying languages like Python, R, SQL/Hive, Java
- Helpful to understand distributed file systems, scalable datastores, distributed computing and related technologies (Spark, Hadoop, etc.)
- Helpful to be familiar with cloud computing, AWS specifically in a distributed computing context
- Helpful to be able to effectively communicate and engage with a variety of partners
Benefits
- Medical, dental, and vision insurance options
- Travel discounts
- Wellness reimbursement
- Restricted Stock Units
- Employee Assistance Program and other mental health support
- Generous time-off
- Parental leave
- Flexible work model
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