Top AI & Machine Learning Jobs in Seattle, WA

Build and deploy enterprise-scale GenAI, RAG, multimodal, and multi-agent systems for growth marketing. Responsibilities include LLM training and adaptation, memory and retrieval architectures, behavioral embeddings, agentic interfaces, observability, safety, evaluation, and scalable production inference. The role requires end-to-end AI product development, collaboration with product and engineering teams, technical leadership, mentoring, and external representation through publications, patents, conferences, or open-source contributions.

Lead design, development, and evaluation of multi-step agentic AI systems (autonomous agents, orchestration, tool use, memory, multi-agent collaboration). Integrate LLMs with external tools/APIs/databases, define evaluation frameworks, mitigate safety risks, and deliver production-grade solutions while mentoring ML staff.

Build and operate production agentic AI experiences for travel discovery, itinerary planning, personalization, and booking. Responsibilities span agent orchestration, backend services, APIs, data and retrieval systems, web experiences, evaluation, observability, safety, and production operations. The role owns product outcomes from ambiguous problem definition through launch and iteration, partners cross-functionally, mentors teammates, and establishes reusable patterns for reliable AI workflows.

Lead research, design, and production deployment of large-scale search and recommendation ML systems, including multi-modal retrieval, multi-stage ranking, personalization, sequential recommenders, evaluation (A/B testing, counterfactuals), and mentoring scientists while partnering with engineering and product teams.

Designs, builds, and operates scalable machine learning platform capabilities across feature engineering, model training, inference, monitoring, and lifecycle management. The role delivers reliable software and infrastructure, improves platform performance and observability, influences architecture and technical standards, and partners with engineering stakeholders to safely integrate AI/ML solutions at scale.

Leads the vision, strategy, and roadmap for AI-powered Brand Expedia experiences across trip inspiration, planning, booking, and travel. Owns experimentation, business outcomes, responsible AI standards, model evaluation, platform partnerships, and third-party AI integrations. Collaborates with engineering, science, design, marketing, and brand teams while coaching product managers and shaping scalable consumer experiences across Expedia’s portfolio.

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.