Staff/Principal Machine Learning Scientist - Ranking & Retrieval in London

Staff/Principal Machine Learning Scientist - Ranking & Retrieval in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
Tripadvisor

At a Glance

  • Tasks: Lead machine learning strategies to enhance travel discovery for millions of users.
  • Company: Join Tripadvisor, a global leader in travel experiences and technology.
  • Benefits: Flexible remote work, competitive pay, tuition assistance, and travel perks.
  • Other info: Collaborative culture focused on innovation and personal growth.
  • Why this job: Make a real impact on how people explore the world with cutting-edge AI.
  • Qualifications: Ph.D. or Master’s in a quantitative field with 8+ years of ML experience.

The predicted salary is between 63000 - 77000 £ per year.

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 retrieval, and multi-modal representation learning.
  • Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP).

Desired:

  • Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings to map complex relations between travel entities (e.g., users, destinations, itineraries, points of interest).
  • Agentic AI & Generative AI: 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, specifically handling non-linear user journeys and highly constrained inventory (e.g., hotel availability, tour timings).
  • A strong track record of academic or industry contributions, including publications in top-tier AI/IR conferences (e.g., SIGIR, KDD, RecSys, NeurIPS) or open-source ML contributions.

What We Offer

  • Competitive compensation packages (routinely benchmarked against the latest industry data), including base salary and annual bonuses.
  • “Work your way” with flexibility to suit your lifestyle. Tripadvisor Group takes a remote-friendly approach to collaboration across a worldwide team, with the option to join on-site as often as you’d like or as required by your team.
  • Flexible schedule. Work-life balance is ingrained in our culture by design. Trust and accountability make it work.
  • Donation matching. Give back? Give more! We match qualifying charitable donations annually.
  • Tuition assistance. Want to level up your career? We love to hear it! Receive annual support for qualified programs.
  • Lifestyle benefit. An annual benefit to spend on yourself. Use it on travel, wellness, or whatever suits you.
  • Travel perks. We believe that travel is employee development, so we provide discounts and more.
  • Employee assistance program. We’re here for you with resources and programs to help you through life’s challenges.
  • Health benefits. We offer great coverage and competitive premiums.
  • Generous referral scheme. Help us grow and be rewarded with generous awards for referring successful candidates.

Our Cultural Pillars:

  • Traveler first: We exist to create value for our customer, the traveler. We enable our suppliers and partners to unlock this value. Their collective behaviors and insights are what drives us.
  • Execution is our edge: We act fast, experiment, learn from failure, iterate, and improve the solutions of tomorrow across every aspect of our business. Our execution is agile, data-driven, prioritised, and built to scale. We assume no problem is someone else’s problem and finish what can be done today, knowing tomorrow will bring fresh challenges.
  • We succeed together: The best outcomes are driven by empathic, humble, and diverse subject matter experts working toward shared goals. We collaborate relentlessly, challenge assumptions, give actionable feedback, and set each other up for success through empowered teams with a clear charter. We transparently take ownership of our growth, individually and as a team. We celebrate the quality of our effort, our learnings, and our collective achievements.

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at AccessibleRecruiting@tripadvisor.com. If you have any additional questions about careers at Tripadvisor you can email us at recruitment@tripadvisor.com. We have all the answers!

Staff/Principal Machine Learning Scientist - Ranking & Retrieval in London employer: Tripadvisor

At TheFork, we pride ourselves on being an exceptional employer that champions a vibrant work culture and prioritises employee growth. Our fully remote position allows you to thrive in a flexible environment while connecting with a diverse team across Europe, all dedicated to enhancing the dining experience. With strong core values guiding our operations, we offer unique opportunities for personal and professional development, making us an ideal choice for those seeking meaningful and rewarding employment.

Tripadvisor

Contact Details:

Tripadvisor Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff/Principal Machine Learning Scientist - Ranking & Retrieval in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Tripadvisor!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Staff/Principal Machine Learning Scientist - Ranking & Retrieval at Tripadvisor.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Tripadvisor.

Apply Directly through Our Website

When you find a suitable opening like Staff/Principal Machine Learning Scientist - Ranking & Retrieval at Tripadvisor, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Staff/Principal Machine Learning Scientist - Ranking & Retrieval in London

Machine Learning Strategy
Deep Multi-Task Ranking
Sequential User Modelling
Graph-Based Travel Recommendations
Recommendation Systems
Multi-Task Learning (MTL)
Multi-gate Mixture-of-Experts (MMoE)

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Tripadvisor, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Tripadvisor. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Tripadvisor

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Tripadvisor!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.