Lead ML Scientist β€” Travel Tech Discovery Engines (Hybrid)

Lead ML Scientist β€” Travel Tech Discovery Engines (Hybrid)

Full-Time 72000 - 88000 Β£ / year (est.) Home office (partial)
Tripadvisor

At a Glance

  • Tasks: Lead ML strategy and execution for travel discovery engines, solving complex AI problems.
  • Company: Tripadvisor, a leader in travel tech with a focus on innovation.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Join a dynamic team at the forefront of travel technology.
  • Why this job: Make a real impact on how millions discover and organise their travel experiences.
  • Qualifications: Expertise in machine learning and experience mentoring high-performing teams.

The predicted salary is between 72000 - 88000 Β£ per year.

Tripadvisor is seeking a Principal Machine Learning Scientist to serve as the technical anchor for our core discovery engine within the Trips vertical. You will steer ML strategy and execution powering how millions search, discover, and organize travel itineraries, blending state-of-the-art AI with production-grade engineering.

You will tackle complex problems in deep multi-task ranking, sequential user modeling, and graph-based travel recommendations, mentoring a high-performing team.

Lead ML Scientist β€” Travel Tech Discovery Engines (Hybrid) 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

We think you need these skills to ace Lead ML Scientist β€” Travel Tech Discovery Engines (Hybrid)

Machine Learning
AI Integration
Deep Learning
Multi-task Ranking
Sequential User Modeling
Graph-based Recommendations
Technical Leadership