Staff/Principal Machine Learning Scientist - Ranking & Retrieval
TripAdvisorResponsibilities
- Drive the technical roadmap for search, retrieval, ranking, and recommendation systems within the Trips vertical.
- Design, prototype, and scale sequential recommendation, representation learning, and deep multi-objective ranking models.
- Oversee low-latency, high-throughput multi-stage retrieval and ranking pipelines processing billions of travel data points in real time.
- Translate business goals into scalable ML architectures and production systems.
- Partner with product managers, engineering leads, and data science teams on multi-task business objectives.
- Mentor and coach senior and mid-level ML scientists and establish best practices for MLOps, A/B testing, data privacy, and code quality.
Requirements
- Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field.
- At least 8 years of industry experience developing and deploying large-scale machine learning models in production.
- Proven experience shipping ML systems serving millions of active users.
- Deep theoretical and practical knowledge of retrieval and ranking, including Multi-Task Learning, Multi-gate Mixture-of-Experts, or similar architectures.
- Hands-on experience building sequential recommendation systems using session dynamics and long-term user preferences.
- Deep understanding of embedding generation, semantic retrieval, and multi-modal representation learning.
- Mastery of Python and deep learning frameworks such as TensorFlow and PyTorch, plus distributed computing with Spark or Ray and cloud infrastructure with AWS or GCP.
- Strong experience with graph neural networks, knowledge graphs, or graph embeddings is desired.
- Familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents is desired.
- Experience in e-commerce, travel technology, or two-sided marketplaces is desired.
- Academic or industry contributions such as publications at SIGIR, KDD, RecSys, or NeurIPS, or open-source ML contributions, are desired.
Benefits
- Competitive compensation packages with base salary and annual bonuses.
- Remote-friendly worldwide collaboration with the option to work on-site as often as desired or required by the team.
- Flexible schedule and work-life balance support.
- Annual matching for qualifying charitable donations.
- Annual tuition assistance for qualified programs.
- Annual lifestyle benefit usable for travel, wellness, or other personal needs.
- Travel discounts and other employee travel perks.
- Employee assistance program.
- Health benefits with competitive premiums.
- Referral awards for successful candidate referrals.
Tech Stack
Categories
About TripAdvisor
Tripadvisor, the world's largest travel guidance platform*, helps hundreds of millions of people each month** become better travelers, from planning to booking to taking a trip. Travelers across the globe use the Tripadvisor site and app to discover where to stay, what to do and where to eat based on guidance from those who have been there before. With more than 1 billion reviews and opinions of nearly 8 million businesses, travelers turn to Tripadvisor to find deals on accommodations, book experiences, reserve tables at delicious restaurants and discover great places nearby. As a travel guidance company available in 43 markets and 22 languages, Tripadvisor makes planning easy no matter the trip type. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), own and operate a portfolio of travel media brands and businesses, operating under various websites and apps, including the following: www.bokun.io, www.cruisecritic.com, www.flipkey.com, www.thefork.com, www.helloreco.com, www.holidaylettings.co.uk, www.jetsetter.com, www.niumba.com, www.seatguru.com, www.singleplatform.com, www.vacationhomerentals.com, www.viator.com. * Source: SimilarWeb, unique users de-duplicated monthly, September 2023 ** Source: Tripadvisor internal log files