Top AI & Machine Learning Jobs

Design, build, and operate scalable backend and ML-enabled services for Expedia's advertiser platform. Productionize ML/LLM features (recommendations, ranking, forecasting, RAG), own APIs, data/feature pipelines, monitoring, and lead cross-functional delivery and engineering best practices.

Lead strategy and execution for Expedia Groups Business-to-Agent channel, building theses, roadmaps, experiments, and productionalizing agent-facing product features. Drive agent legibility, indexing, and agent-preference research, partner cross-functionally, lead a senior-engineer squad, and communicate outcomes to executives.

Own marketing measurement strategy for Paid Social, Programmatic, and Paid App channels. Design experimentation, incrementality, attribution, and marketing mix modeling frameworks; analyze data with SQL, Python, and Tableau; identify growth opportunities; and translate findings into recommendations for senior leadership and multimillion-dollar investment decisions. Partner cross-functionally to implement scalable measurement solutions, establish analytics standards, influence marketing ROI practices, and mentor team members.

Develop and productionize machine learning systems for personalization, ranking, recommendations, retrieval, and adaptive customer experiences. Design experiments, evaluate model performance, engineer features, prepare data, and improve model quality. Collaborate with engineering, product, analytics, and science teams on scalable ML services, APIs, data models, deployment, monitoring, and operational performance. Apply deep learning, recommender systems, sequential modeling, embeddings, experimentation, and MLOps practices in large-scale consumer environments.

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 deploy scalable machine learning solutions for personalization, recommendation, ranking, retrieval, and traveler understanding. Lead end-to-end scientific work spanning data exploration, feature engineering, model development, experimentation, evaluation, and productionization. Partner with engineering, product, and business teams on system and API integration, improve model reliability and operational quality, influence technical direction, mentor scientists, and apply advanced methods including neural recommenders, foundation models, LLMs, and representation learning.

Lead end-to-end strategy, roadmap, technical execution, and measurement for Answer Engine Optimization (AEO). Own retrieval, indexing, bot access, measurement systems, and productization; drive cross-functional engineering, market intelligence, and executive communications to optimize visibility and commercial outcomes with frontier LLMs and agentic search.

Lead technical vision and architect an AI-native agentic marketing platform. Build agent-facing indices, APIs, observability, and experimentation; ship 0-to-1 agent-specific products; operate a small engineering squad; mentor engineers; ensure resilient, secure, and cost-efficient systems integrated with AI tooling and third-party platforms.

Design, build, and operate scalable ML systems and services end-to-end: data sourcing, feature engineering, model development, deployment, monitoring, and operational support. Collaborate across product, data, and engineering, drive ML best practices, and mentor other engineers to improve model reliability, performance, and observability.

Senior individual contributor providing analytics and decision support for Localization product. Design and lead A/B and causal experiments, build and deploy production ML/NLP models, and develop scalable SQL/Python analytics pipelines and dashboards. Translate multilingual insights for stakeholders, mentor junior staff, and co-own metric frameworks and ML-enabled solutions.