Sundayy
Machine Learning Scientist
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
About The Company
Tripadvisor is a leading global travel platform dedicated to connecting travelers with memorable experiences. As part of the Tripadvisor Group, which includes renowned brands such as Viator and TheFork, the company leverages innovative technology, rich content, and comprehensive travel guidance to facilitate seamless travel planning and discovery. With a mission to become the world's most trusted source for travel information, Tripadvisor empowers millions of users worldwide to explore destinations, book accommodations, discover local attractions, and share their travel stories. The organization fosters a culture of innovation, collaboration, and inclusivity, constantly striving to enhance user experience and deliver value to both travelers and partners across the travel ecosystem.
About The Role
The Principal Machine Learning Scientist role is a strategic and technical leadership position based in London, United Kingdom. This individual will serve as the core driver of machine learning initiatives within the Trips vertical, focusing on enhancing the company's core discovery engine. The role entails leading the design, development, and deployment of large-scale, high-performance machine learning models that influence how millions of users search, discover, and organize their travel itineraries. The ideal candidate will possess a deep expertise in AI research and practical engineering, capable of translating complex business needs into scalable ML solutions. They will oversee the technical roadmap, foster cross-functional collaboration, and mentor a talented team of scientists, all while ensuring the delivery of innovative, efficient, and impactful AI systems that improve user engagement, booking conversions, and overall platform performance.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field
- Minimum of 8+ years of industry experience developing and deploying large-scale machine learning models in production environments
- Proven track record of delivering systems that support millions of active users
- Deep theoretical and practical knowledge in retrieval and ranking algorithms, multi-task learning, and advanced recommendation systems
- Experience with sequential and temporal user modeling, representation learning, and multi-modal data integration
- Expertise in deep learning frameworks such as TensorFlow and PyTorch
- Hands-on experience with distributed computing platforms like Spark and Ray, and cloud services such as AWS or GCP
- Strong understanding of graph neural networks, knowledge graphs, and graph embeddings
- Familiarity with agentic AI, large language models, and autonomous planning agents
- Experience working in travel tech, e-commerce, or two-sided marketplaces with complex user journeys and constrained inventories
- Excellent communication and leadership skills, with a history of mentoring and coaching teams
- Published research in top-tier AI and information retrieval conferences (e.g., SIGIR, KDD, NeurIPS) or significant open-source contributions
Responsibilities
- Define and execute the technical roadmap for ML-driven Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical
- Design, prototype, and scale innovative recommendation and ranking models to solve complex travel-related problems
- Develop advanced algorithms utilizing sequential recommenders, representation learning, and multi-objective frameworks to enhance user experience
- Oversee the deployment of low-latency, high-throughput data pipelines capable of processing billions of travel data points in real-time
- Collaborate closely with Product Managers, Engineering Leads, and Data Science teams to align ML initiatives with business objectives
- Act as the primary technical authority for ML projects, ensuring best practices in model development, deployment, and maintenance
- Mentor and coach senior and mid-level ML scientists, fostering a culture of technical excellence and continuous learning
- Promote and implement best practices in MLOps, data privacy, rigorous A/B testing, and code quality
- Stay abreast of emerging AI research and industry trends, integrating relevant advancements into Tripadvisor’s technology stack
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Benefits
- Competitive compensation packages including base salary and annual bonuses
- Flexible work arrangements supporting remote collaboration and on-site presence as needed
- Work-life balance initiatives, including flexible scheduling and a supportive culture
- Annual donation matching for charitable contributions
- Tuition assistance programs for professional development
- Lifestyle benefits, including wellness allowances and travel discounts
- Comprehensive health insurance coverage
- Employee assistance programs offering support for personal and professional challenges
- Referral incentives for successful candidate recommendations
Equal Opportunity
Tripadvisor is committed to fostering an inclusive environment that values diversity and equal opportunity. We welcome applications from candidates of all backgrounds and experiences. We believe that diverse teams drive innovation and excellence, and we are dedicated to creating a workplace where everyone can thrive.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location