Senior Machine Learning Scientist

About the role

You will lead technical strategy for the discovery engine within the Experiences R&D team. This role focuses on building and deploying machine learning solutions for search, ranking, and content AI to improve travel planning for millions of users. You will own the end to end lifecycle of high impact ML initiatives, translating ambiguous business goals into scalable technical solutions. A key part of this position involves setting the technical direction for model development and ensuring alignment with product and engineering roadmaps. You will drive innovation by researching and prototyping novel methods that directly enhance how travelers explore and book experiences. Collaboration with cross functional partners is central, as you will work closely to integrate machine learning into production systems with strict reliability standards. Success in this role will be measured by the quality of the models, their impact on user engagement, and the robustness of the pipelines you establish.

Key facts

What you'll do

• Lead ML projects by designing custom model components and loss functions that directly address business objectives in travel discovery.
• Evaluate new architectures through rigorous cost-benefit analysis, focusing on inference speed, memory footprint, and execution costs to ensure feasibility.
• Optimize models using distillation and quantization techniques to reduce latency and resource consumption without sacrificing accuracy.
• Develop and maintain golden datasets, leaderboards, and automated validation frameworks to prevent production regressions and ensure data integrity.
• Partner with engineering teams to define model failure modes and infrastructure requirements, establishing clear guardrails for deployment.
• Diagnose algorithmic issues in production and implement automated checks for concept drift or feature distribution shifts to maintain model health.
• Mentor mid-level and associate scientists on experimental logic, helping them grow their skills within production constraints and best practices.
• Design experiments that isolate key variables in user behavior, enabling data driven decisions for search and ranking improvements.
• Contribute to the creation of scalable data pipelines that feed into model training workflows, ensuring efficient and reliable data flows.
• Champion the use of monitoring tools to track model performance over time and surface anomalies as early warnings.
• Translate complex model outputs into actionable insights for non technical stakeholders, bridging the gap between data science and product teams.
• Explore opportunities to leverage foundation models and emerging techniques to enhance the travel planning experience in novel ways.
• Ensure that all solutions adhere to strict quality standards, maintaining consistency and reliability across the platform.
• Act as a technical thought leader within the organization, influencing best practices for machine learning engineering and research.

Requirements

• Hold a Master's or Ph.D. in Computer Science, Statistics, Machine Learning, or a related quantitative field with a strong theoretical background.
• Bring 5+ years of industry experience in developing and deploying large scale ML models in production environments.
• Demonstrate mastery of Python and deep learning frameworks such as PyTorch, PyTorch Lightning, or TensorFlow with advanced proficiency.
• Show a strong foundation in feature engineering, model architecture design, and deep learning techniques across diverse problem domains.
• Prove the ability to adapt state of the art architectures to solve complex business problems while balancing tradeoffs between performance and cost.
• Exhibit excellent problem solving skills, with the capacity to debug intricate issues in data, models, and deployment pipelines.
• Communicate effectively, both in writing and verbally, to articulate technical concepts to both technical and non technical audiences.
• Work comfortably in a fast paced, dynamic environment where priorities may shift based on business needs and research insights.

Nice to have

• Experience with multi task learning, ranking systems, and Content AI to enhance recommendation quality and user satisfaction.
• Familiarity with Agentic AI and generative workflows, exploring how these paradigms can be integrated into travel planning.
• Expertise in sequential recommendation systems for modeling user session dynamics and improving journey personalization.
• Knowledge of Graph Neural Networks, knowledge graphs, and multi modal representation learning to capture complex relationships in travel data.

Skills & tools

• Python
• PyTorch / PyTorch Lightning / TensorFlow
• Deep Learning
• Machine Learning
• Data versioning and experiment tracking tools

Practical notes

• Compensation includes base salary and annual bonuses, providing a comprehensive total rewards package.
• Benefits include flexible scheduling, tuition assistance, lifestyle stipends, travel discounts, donation matching, and health coverage to support overall wellbeing.
• The company offers a remote friendly, hybrid work environment, allowing flexibility in how and where you work.
• For reasonable accommodations during the application process, candidates are encouraged to contact AccessibleRecruiting@tripadvisor.com for support.
• For general career questions regarding the role or application status, recruitment@tripadvisor.com is available to assist.
• This position is based in London, United Kingdom, with hybrid work expectations that balance in office collaboration and remote flexibility.
• The selection process may include technical assessments and interviews designed to evaluate both practical skills and conceptual understanding.
• Interested candidates should apply promptly to ensure full consideration, as timelines are aligned with business needs.
• All employment decisions are based on merit and the successful demonstration of required qualifications and capabilities.