Principal Machine Learning Scientist

tripadvisor · Londonlead

En corto

▸Científico de ML Principal que dirige el motor de descubrimiento de viajes a gran escala.
▸Diseña modelos avanzados de recomendación, clasificación y búsqueda con enfoque en itinerarios complejos y comportamiento secuencial.
▸Destaca por liderar IA de punta con impacto directo en conversiones y participación de usuarios.

Proficiency in English is required.

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¿Qué piden?

✓Doctorado o máster en Ciencias de la Computación, ML, Estadística o campo cuantitativo.
✓8+ años en desarrollo y despliegue de modelos ML a gran escala con usuarios activos en millones.
✓Experiencia práctica con Multi-Task Learning (MTL) y arquitecturas como MMoE.
✓Habilidades sólidas en modelado secuencial y temporal del usuario.
✓Conocimiento profundo en aprendizaje de representaciones y búsqueda semántica.
✓Capacidad para liderar técnicamente y mentorizar equipos de científicos de datos.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

Multi-Task LearningMMoESequential RecommendersRepresentation LearningVector SearchMulti-Stage RetrievalDeep Semantic RetrievalReal-Time ProcessingA/B TestingMLOps

¿A quién escribirle en tripadvisor?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

About Tripadvisor The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork. About the role: As a Principal Machine Learning Scientist , you will be the technical anchor for our core discovery engine. You will lead the machine learning strategy and execution that powers how millions of users search for, discover, and organize their complex travel itineraries. This is a high-impact role bridging the gap between cutting-edge AI research and production-grade engineering, directly influencing multi-objective business outcomes like user engagement, booking conversion, etc. You will tackle complex, ambiguous problems at the intersection of deep multi-task ranking, sequential user modeling, and graph-based travel recommendations. If you are passionate about building state-of-the-art AI systems and mentoring a high-performing team of scientists, this role is for you What You'll Do • Technical Leadership & Execution: Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical. Translate high-level business goals into concrete ML architectures and scalable production systems. • Advanced Algorithm Innovation: Design, prototype, and scale next-generation recommendation and ranking models. Solve complex, non-linear travel journeys by utilizing sequential recommenders, representation learning, and deep multi-objective frameworks. • System Architecture & Scalability: Oversee the deployment of low-latency, high-throughput retrieval and ranking pipelines (e.g., multi-stage retrieval, vector search) capable of processing billions of travel data points (reviews, photos, bookings, user intent) in real-time. • Cross-Functional Collaboration: Partner closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi-task business objectives simultaneously. Act as the primary technical authority for ML initiatives within the Trips vertical. • Talent Multiplier: Mentor and coach senior and mid-level ML scientists. Foster a culture of technical excellence, driving best practices for MLOps, rigorous A/B testing, data privacy, and code quality. Skills & Experience: • Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field. • Experience: 8+ years of industry experience developing and deploying large-scale ML models in a production environment, with a proven track record of shipping systems at the scale of millions of active users. • Core Technical Expertise: Deep theoretical and practical knowledge in the following areas: • SOTA Retrieval & Ranking: Practical experience with Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar architectures optimized for multi-objective optimization. • Sequential & Temporal Modeling: Hands-on experience building sequential recommendation systems that capture real-time user session dynamics and long-term historical preferences. • Advanced Representation Learning: Deep understanding of embedding generation, deep semantic retrie

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