Staff/Principal Machine Learning Scientist

Salary: £71,000 - 99,000 per year

Requirements

• We require a Ph.D. or Masters degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field.
• We require 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.
• We need deep theoretical and practical knowledge of SOTA retrieval and ranking, including Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar multi-objective architectures.
• We need hands-on experience building sequential recommendation systems that capture real-time user session dynamics and long-term historical preferences.
• We need deep understanding of embedding generation, deep semantic retrieval, and multi-modal representation learning.
• We require mastery of Python and deep learning frameworks such as TensorFlow and PyTorch, along with hands-on experience with distributed computing tools like Spark and Ray and cloud infrastructure such as AWS or GCP.
• We prefer experience with Graph Neural Networks, knowledge graphs, or graph embeddings for modeling complex relations between travel entities.
• We prefer familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents.
• We prefer experience in E-commerce, Travel Tech, or Two-Sided Marketplaces, especially with non-linear user journeys and constrained inventory.
• We prefer a strong track record of academic or industry contributions, including publications in top-tier AI/IR conferences or open-source ML contributions.

Responsibilities

• We serve as the technical anchor for our core discovery engine.
• We lead the machine learning strategy and execution that powers how millions of users search for, discover, and organize their complex travel itineraries.
• We bridge cutting-edge AI research and production-grade engineering to influence multi-objective business outcomes such as user engagement and booking conversion.
• We drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical.
• We translate high-level business goals into concrete ML architectures and scalable production systems.
• We design, prototype, and scale next-generation recommendation and ranking models.
• We solve complex travel journeys using sequential recommenders, representation learning, and deep multi-objective frameworks.
• We oversee the deployment of low-latency, high-throughput retrieval and ranking pipelines, including multi-stage retrieval and vector search, capable of processing billions of travel data points in real time.
• We partner closely with Product Managers, Engineering Leads, and Data Science peers to optimize multiple business objectives simultaneously.
• We act as the primary technical authority for ML initiatives within the Trips vertical.
• We mentor and coach senior and mid-level ML scientists.
• We foster best practices for MLOps, rigorous A/B testing, data privacy, and code quality.

Technologies

• Agentic AI
• AI
• AWS
• Cloud
• GCP
• LLM
• Machine Learning
• MLOps
• PyTorch
• Python
• Spark
• TensorFlow
• Support

More

We are Tripadvisor Group, connecting people to experiences worth sharing and aiming to be the worlds most trusted source for travel and experiences. Our portfolio includes Tripadvisor, Viator, and TheFork, and we use our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces across travel categories. We offer competitive compensation, remote-friendly flexibility with optional on-site collaboration, a flexible schedule, donation matching, tuition assistance, an annual lifestyle benefit, travel perks, an employee assistance program, health benefits, and a generous referral scheme. Our culture is built around traveler first, execution as our edge, and succeeding together, with an accessible and inclusive candidate experience.

last updated 34 week of 2026