Tripadvisor
Travel
SeniorMachineLearningScientist
“Senior Machine Learning Scientist at Tripadvisor. Skills: Machine Learning, Deep Learning, Production Deployment, Algorithmic Optimization. Serve as technical lead. Own and execute ML strategy”
What You'll Achieve.
Map offline model metrics directly to business KPIs like booking conversion and user engagement
Industry & Context.
Navigate technical ambiguity; Diagnose complex algorithmic bugs; Resolve blocking corrective actions
What They're Looking For.
Must Have
Master's or Ph.D. degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field, 5+ years of industry experience developing, validating, and deploying large-scale ML models in production environments, practical and theoretical foundation in machine learning techniques, feature engineering, deep learning paradigms, Python, deep learning frameworks
Nice to Have
Experience with multi-task learning (MTL), ranking, Content AI stacks, Agentic AI, Next-generation retrieval pipelines, multi-stage ranking systems, Content AI stacks, Advanced sequential recommendation systems, Graph Neural Networks (GNNs), knowledge graphs, multi-modal representation learning, Generative AI, Agentic AI workflows
What You'll Do.
Serve as technical lead
Own and execute ML strategy
Design and implement custom model components
Implement custom algorithmic components
Map offline model metrics to business KPIs
Evaluate global research landscape
Conduct cost-benefit analyses
Optimize models for production
Tailor Golden Datasets
Implement rigorous validation automation
Define model failure modes
Diagnose complex algorithmic bugs
Implement automated checks
Lead team-level post-mortems
Resolve blocking corrective actions
Mentor mid-level and associate ML scientists
Review experimental logic
Guide through applied ML
Guide through production constraints
How You'll Work.
Team & Collaboration
Collaborate closely with Engineering Leads; Enable SWE partners to build robust fallback systems; Work toward shared goals; Collaborate relentlessly; Challenge assumptions; Give actionable feedback; Set each other up for success
Communication Scope
Clearly define model failure modes
Process & Methodology
Break down massive research goals into deliverable, iterative milestones
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