Location
London (Remote-friendly with option to join on-site as desired or required)

Hours
Flexible schedule to suit your lifestyle

Salary
Negotiable

About the Role
As a Senior Machine Learning Scientist at Tripadvisor Experiences R&D Team, you will be a key technical lead and pod architect within our core discovery engine. You will independently own and execute the machine learning strategy for major product capabilities such as Search, Retrieval, Ranking, or Content AI that power how millions of users discover and plan their travel itineraries. This role bridges the gap between state-of-the-art research and robust, production-grade engineering. You will navigate technical ambiguity, implement custom algorithmic components, and explicitly map offline model metrics directly to business KPIs like booking conversion and user engagement. If you are a relentlessly curious scientist who excels at rapid prototyping, practical deployment of SOTA models, and multiplying the capabilities of your peers, this role is for you.

What You’ll Do
- Act as the technical lead for specific ML projects within your pod, designing and implementing custom model components or loss functions.
- Evaluate the global research landscape to conduct cost-benefit analyses on new architectures, balancing model complexity against inference speed, memory usage, and execution costs.
- Optimize models for production using techniques like quantization and distillation.
- Tailor Golden Datasets and leaderboards with minimal supervision and implement rigorous validation automation to prevent data leakage, over-fitting, and production regressions.
- Collaborate closely with Engineering Leads to ensure infrastructure supports model requirements and define model failure modes and confidence thresholds.
- Diagnose complex algorithmic bugs and implement automated checks for silent failures such as concept drift or feature distribution shifts.
- Lead team-level post-mortems and resolve blocking corrective actions.
- Mentor mid-level and associate ML scientists, reviewing experimental logic and guiding them through applied ML and production constraints.

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 a global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. Our portfolio includes Tripadvisor, Viator, and TheFork. With over 400,000 travel experiences available, we make it easier than ever for travelers to create lasting memories.

What We Offer
- Competitive compensation packages including base salary and annual bonuses.
- Flexible work arrangements with a remote-friendly approach.
- Work-life balance ingrained in our culture.
- Donation matching for qualifying charitable donations.
- Tuition assistance for qualified programs.
- Annual lifestyle benefit to spend on travel, wellness, or other personal interests.
- Travel perks and discounts.
- Employee assistance program.
- Comprehensive health benefits with competitive premiums.
- Generous referral scheme to reward successful candidate referrals.

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

Experience
5+ years of industry experience developing, validating, and deploying large-scale machine learning models in production environments.

About you
- Relentlessly curious scientist with strong practical and theoretical foundation in machine learning techniques, feature engineering, and deep learning paradigms.
- Proven ability to adapt and hybridize state-of-the-art architectures to solve complex business problems.
- Experience with multi-task learning, ranking, Content AI stacks, and Agentic AI is highly desirable.
- Skilled in rapid prototyping, practical deployment, and mentoring peers.
- Strong collaboration skills to work closely with engineering teams and cross-functional partners.

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

Technical Stack
- Mastery of Python and deep learning frameworks such as PyTorch, PyTorch Lightning, or TensorFlow.
- Familiarity with data versioning and experiment tracking tools.
- Experience with next-generation retrieval pipelines, multi-stage ranking systems, Content AI stacks, advanced sequential recommendation systems, Graph Neural Networks, knowledge graphs, multi-modal representation learning, Generative AI, and Agentic AI workflows is a plus.