Engine is looking to revolutionize work travel by transforming how businesses and their teams experience travel through a modern travel platform. The company aims to build a world-class data science team focused on transforming how millions of business travelers discover and book their perfect trips by architecting search and personalization systems.
Requirements
- 7+ years of industry experience in data science/ML engineering, with at least 4+ years specifically focused on search, ranking, and personalization systems at scale.
- Deep hands-on experience with recommendation systems, including collaborative filtering, content-based filtering, hybrid approaches, and modern deep learning techniques (neural collaborative filtering, transformer-based models, two-tower architectures).
- Proven track record building learning-to-rank models, query understanding systems, and search relevance optimization in production environments.
- Expert-level proficiency in Python (PyTorch/TensorFlow), distributed computing (Spark), and modern ML infrastructure.
- Experience with real-time serving systems and vector databases.
- Experience in travel, e-commerce, or marketplace platforms
- Experience with multi-objective optimization and contextual bandits
Responsibilities
- Architect and build Engine's personalization engine from the ground up, implementing state-of-the-art recommendation systems, collaborative filtering, and deep learning models to deliver hyper-relevant search results and travel recommendations.
- Drive search conversion optimization through advanced ranking algorithms, query understanding, and real-time personalization, directly impacting Engine's core business metrics.
- Lead the development of user embedding and preference modeling systems that capture complex traveler behaviors, corporate policies, and contextual signals to power personalized experiences across the platform.
- Build and mentor a world-class data science team as a founding member, establishing best practices, technical standards, and a culture of experimentation and innovation.
- Partner with product, engineering, and business leaders to define the search and personalization roadmap, translating business objectives into sophisticated ML solutions.
- Design and implement A/B testing frameworks and experimentation infrastructure to rapidly iterate on personalization strategies and measure impact.
- Develop real-time inference systems that can deliver personalized results at scale with sub-second latency requirements.
Other
- Experience as a technical lead or founding member of a data science team, with the ability to balance hands-on contribution with strategic thinking and team building.
- Demonstrated success improving key business metrics (conversion, engagement, retention) through personalization, with the ability to communicate complex technical concepts to executive stakeholders.
- MS/PhD in Computer Science, Machine Learning, Statistics, or related quantitative field, or equivalent industry experience building production ML systems.
- Publications or patents in personalization, recommendation systems, or information retrieval
- Knowledge of privacy-preserving personalization techniques
