Senior Machine Learning Scientist – Personalization

Expedia Group

. Design, develop, and apply machine learning solutions to real-world personalization, product, and business problems .

Posted 10/13/2026full-timeUnited StatesSenior💰 $173,000 - $261,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing machine learning solutions, with a strong focus on model development, evaluation, and operationalization. Proven ability to collaborate with cross-functional teams to integrate AI/ML solutions into business workflows and enhance personalization systems.

Highest-signal resume keywords

Machine Learning Solutions OwnershipModel Development and EvaluationData Modeling and IntegrationDeep Learning Systems for PersonalizationCross-Functional Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning MethodsStatistical AnalysisData-Driven Decision MakingFeature EngineeringModel Lifecycle ManagementNeural Recommendation SystemsTransformer-Based RecommendersGenerative RetrievalFoundation ModelsEmbedding Models

Soft Skills

MentoringDocumentationExperimentation

Tools & Technologies

API DesignData ExplorationProduction MonitoringOperational Excellence

Certifications & Qualifications

Bachelor's Degree in Computer ScienceAdvanced Degree in Machine Learning or Related Field

Industry Keywords

PersonalizationRecommendation SystemsE-CommerceMarketplaceSearchAds

About the role

Key responsibilities & impact

Design, develop, and apply machine learning solutions to real-world personalization, product, and business problems
Translate ambiguous opportunities into scalable models, experiments, and production-ready capabilities
Drive end-to-end scientific work across problem formulation, data exploration, feature engineering, model development, evaluation, and iteration
Partner with engineers, product, and business stakeholders to integrate machine learning solutions into services and workflows
Contribute to system design, API design, and data modeling considerations where applicable
Select appropriate methods, validate outcomes, and improve model performance, reliability, and operational quality
Safely integrate and operate AI/ML-enabled solutions that improve outcomes
Contribute technical expertise through experimentation, documentation, mentoring, and reusable approaches
Help shape deep learning systems for personalization, including recommendation, ranking, retrieval, traveler understanding, sequential modeling, and foundation-model-based personalization
Influence technical direction, raise the modeling bar, and mentor other scientists

Requirements

What you’ll need

Bachelor's degree in Computer Science or a related technical field; or equivalent related professional experience
8+ years of relevant professional experience
Demonstrated ownership of machine learning solutions at the service or multi-service level, including problem definition, model development, evaluation, and operationalization
Strong foundation in machine learning methods, statistical analysis, experimentation, and data-driven decision making
Hands-on coding experience in scientific and production-oriented environments
Experience working with cross-functional partners to deploy technical solutions
Experience with scalable model development, data modeling, and integration into software systems
Preferred: advanced degree in Machine Learning, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
Preferred: experience delivering machine learning solutions at scale, including architecture considerations, production monitoring, model lifecycle management, and operational excellence
Preferred: experience with recommendation, ranking, retrieval, search, personalization, ads, marketplace, e-commerce, or similarly complex applied ML systems
Preferred: experience with neural recommendation systems, sequential or session-based recommendation, transformer-based recommenders, semantic retrieval, generative retrieval, or representation learning at scale
Preferred: experience with foundation models, LLMs, embedding models, semantic IDs, hybrid LLM-recommender systems, two-stage retrieval and ranking systems, or retrieval-augmented personalization workflows
Preferred: relevant academic publications, patents, open-source contributions, technical blog posts, industry talks, or other contributions to the ML/recommender-systems community

Benefits

Comp & perks

Medical, dental, and vision coverage
Paid time off
Employee Assistance Program
Wellness reimbursement
Travel reimbursement
Travel discounts
International Airlines Travel Agent Network (IATAN) membership
Accommodation or adjustment support during the application or recruiting process for disabilities