Location
London

Hours
Full Time

Salary
Negotiable

About the Role
As a Principal Machine Learning Scientist at Tripadvisor, 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 high-impact role bridges cutting-edge AI research and production-grade engineering, directly influencing multi-objective business outcomes such as user engagement and booking conversion. 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
- 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.
- Design, prototype, and scale next-generation recommendation and ranking models.
- Solve complex, non-linear travel journeys using sequential recommenders, representation learning, and deep multi-objective frameworks.
- Oversee deployment of low-latency, high-throughput retrieval and ranking pipelines capable of processing billions of travel data points in real-time.
- Partner closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi-task business objectives.
- Act as the primary technical authority for ML initiatives within the Trips vertical.
- Mentor and coach senior and mid-level ML scientists, fostering a culture of technical excellence and best practices in MLOps, A/B testing, data privacy, and code quality.

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. Leveraging our brands, technology, and capabilities, we connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. Our subsidiaries include a portfolio of travel brands such as Tripadvisor, Viator, and TheFork.

What We Offer
Competitive compensation packages benchmarked against industry data, including base salary and annual bonuses.
Flexible work arrangements with a remote-friendly approach and optional on-site collaboration.
Flexible schedule promoting work-life balance.
Donation matching for qualifying charitable contributions.
Tuition assistance for career development.
Lifestyle benefit to spend on travel, wellness, or personal interests.
Travel perks including discounts.
Employee assistance program for personal support.
Comprehensive health benefits with competitive premiums.
Generous referral scheme rewarding successful candidate referrals.

Our Cultural Pillars
Traveler first: We create value for travelers and enable suppliers and partners to unlock this value.
Execution is our edge: We act fast, experiment, learn, iterate, and improve solutions with agility and data-driven prioritization.
We succeed together: We collaborate with empathy and humility, challenge assumptions, give actionable feedback, and celebrate collective achievements.

Experience
- 8+ years of industry experience developing and deploying large-scale ML models in production environments.
- Proven track record of shipping systems at the scale of millions of active users.
- Practical experience with Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar architectures optimized for multi-objective optimization.
- Hands-on experience building sequential recommendation systems capturing real-time user session dynamics and long-term preferences.
- Deep understanding of embedding generation, deep semantic retrieval, and multi-modal representation learning.
- Mastery of Python and deep learning frameworks (TensorFlow, PyTorch).
- Experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP).

About You
- Strong experience applying Graph Neural Networks (GNNs), knowledge graphs, or graph embeddings to model complex relations between travel entities.
- Familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents to enhance conversational search and automated itinerary generation.
- Experience working in E-commerce, Travel Tech, or Two-Sided Marketplaces, especially handling non-linear user journeys and constrained inventory.
- A strong track record of academic or industry contributions, including publications in top-tier AI/IR conferences or open-source ML contributions.
- Passionate about mentoring and fostering a culture of technical excellence.

Qualifications
Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field.