Top AI & Machine Learning Jobs

Leads the Content AI organization, managing and developing data scientists and machine learning engineers. Oversees machine learning solutions for content generation, moderation, quality, and relevance across text, video, and images. Sets strategy, technical priorities, and team practices while partnering with Product, Engineering, and leadership. Guides production-ready, scalable AI systems, stakeholder communication, delivery optimization, recruiting, performance management, and career development.

Leads an applied science team developing scalable machine learning and data science solutions for pricing and monetization. Responsibilities include architecting models, providing technical guidance, setting strategy and roadmaps, managing execution, hiring and mentoring scientists, and collaborating with engineering, product, analytics, and operations teams. The role also contributes to causal inference, stochastic optimization, demand estimation, and experiment design research.

Develop and productionize machine learning systems for personalization, recommendation, ranking, retrieval, traveler understanding, and sequential modeling. Lead end-to-end scientific work including problem formulation, data exploration, feature engineering, model development, experimentation, evaluation, and operationalization. Collaborate with engineering, product, and business stakeholders on system and API design, mentor other scientists, influence technical direction, and apply advanced deep learning and foundation-model techniques at scale.

Design and productionize machine learning systems for personalization, recommendation, ranking, retrieval, and traveler understanding. Lead end-to-end scientific work from problem formulation and feature engineering through experimentation, evaluation, deployment, and monitoring. Partner with engineering, product, and business stakeholders on scalable system integration, influence technical direction, mentor scientists, and advance deep learning, sequential modeling, foundation-model, and recommender-system capabilities.

Design and maintain scalable ML infrastructure for training, deployment, serving, data pipelines, feature engineering, monitoring, and model performance optimization. Collaborate with data scientists to productionize models, implement MLOps and CI/CD practices, research technologies, mentor junior engineers, and provide technical guidance across teams.

Design, prototype, and evaluate machine learning models for travel products. Build maintainable training and inference code, participate in system and API design, prepare data, conduct feature engineering and error analysis, and collaborate with scientists, engineers, product partners, and mentors to develop reliable ML solutions.

Design, prototype, and evaluate machine learning models; develop maintainable training and inference code; conduct data preparation, feature engineering, statistical analysis, and error analysis; and contribute to ML system, API, and data modeling. Collaborate with scientists, engineers, mentors, and product partners to define metrics and build production-aware, fair, and scalable ML solutions.

Design, prototype, and evaluate machine learning models for travel products. Build maintainable training and inference code, conduct experiments and A/B testing, prepare data, perform feature engineering and error analysis, and contribute to ML system and API design. Collaborate with scientists, engineers, product partners, and mentors to develop scalable, robust, fair, and production-aware AI/ML solutions.

Research and develop scalable machine learning and data science solutions for Vrbo pricing and monetization. The role applies causal inference, operations research, optimization, demand estimation, and experiment design to production systems. Responsibilities include defining performance metrics, analyzing complex datasets, collaborating with scientists, engineers, product managers, and analytics teams, communicating technical plans, and validating models through A/B testing.

Design, prototype, and evaluate machine learning models for travel products. Build maintainable training and inference code, conduct statistical analysis and feature engineering, participate in ML system and API design, and collaborate with data scientists, engineers, mentors, and product partners. Interns will contribute to research and product experiments involving scalable services, A/B testing, fairness, and AI-enabled solutions.