Machine Learning Scientist I, Generative AI

Job Description

Tripadvisor is seeking a Machine Learning Scientist I to join their team in Lisbon, Portugal. This role focuses on Generative AI and will support marketing efforts. The ideal candidate will apply their modeling skills to drive innovation across various problem spaces, including online advertising, customer modeling, experimental design, revenue optimization, attribution, recommendations, content, and creative solutions.

The Machine Learning Scientist I will collaborate with a multidisciplinary team, including other ML scientists, analysts, product managers, and engineers, to build ML-powered solutions and solve concrete business problems. They will have the opportunity to take ownership of projects and identify new opportunities to apply machine learning to improve the business.

Tripadvisor promotes a culture of personal development, offering social activities, journal clubs, memberships in online learning resources, and participation in industry conferences.

What this role involves:

• Participating in the design and deployment of GenAI solutions.
• Seeking out new opportunities to apply GenAI in the Marketing space.
• Staying current with the latest advancements in machine learning.
• Prototyping, evaluating, deploying, and maintaining new models in production.
• Designing A/B tests and analyzing their results.
• Communicating progress and interpretation of model output/performance to technical and business stakeholders.
• Participating in the determination of next steps for each project.

Requirements:

• Master’s degree in Computer Science, Engineering, Statistics, or related quantitative field.
• Excellent communication skills for both technical and non-technical audiences.
• Strong foundation in machine learning and statistics.
• Solid foundation on data structures and algorithms.
• Proficiency in Python.
• Experience with Gen AI projects is a plus.

What this role offers:

• Opportunity to work with the newest development tools and huge datasets.
• Chance to deploy solutions online and observe the impact of work in real-time.
• Collaboration with a broad multidisciplinary team.
• A culture of personal development, including social activities and learning resources.