4 days ago
Responsibilities
- Architect, build, and ship enterprise-scale GenAI, RAG, and multi-agent systems across frontend, backend, and user interfaces.
- Design hierarchical agent ecosystems with interactive generative UIs, dashboards, safety controls, and observability features.
- Develop short-term and long-term memory, knowledge graph augmentation, adaptive retrieval, vector memory, and agent orchestration systems.
- Build LLM evaluation platforms using LLM-as-a-Judge, synthetic data generation, and agent trajectory assessment.
- Train, fine-tune, adapt, and distill LLMs for production chatbots and GenAI products.
- Build multimodal pipelines spanning vision, audio, text, and structured data while optimizing scalability and latency.
- Develop large-scale behavioral embedding and real-time serving systems for personalization, audience targeting, propensity modeling, and next-best-action recommendations.
- Collaborate with product, engineering, and design teams to deliver user-facing features and seamless experiences.
- Mentor engineers and ML scientists, establish technical standards, conduct design reviews, and improve organizational technical maturity.
- Represent the organization through open-source contributions, patents, conferences, and publications.
Requirements
- 10+ years of experience in software engineering, machine learning, and AI systems, including production GenAI deployments.
- Deep expertise in LLM training, adaptation, distillation, RLHF/DPO, and RAG systems.
- Strong NLP foundation and experience with multimodal AI and vision-language models.
- Experience building and operating multi-agent AI platforms with safety and observability frameworks.
- Experience with distributed GPU training and inference, cloud infrastructure, container orchestration, and ML tooling.
- Ability to lead end-to-end AI product development and ship user-facing features with product and design teams.
- Excellent communication skills, including the ability to present complex architecture and product concepts to executives.
- PhD in Computer Science, Machine Learning, or a related field is preferred.
- Industry recognition through publications, patents, talks, or open-source contributions in LLMs, RAG, or agentic systems is preferred.
- Experience with multimodal LLMs involving vision, audio, music, and structured data is preferred.
- Leadership in GenAI safety, evaluation, testing, and monitoring is preferred.
- Strong cross-disciplinary fluency across modeling, infrastructure, product, and design is preferred.
Benefits
- Medical, dental, and vision coverage.
- Paid time off and an Employee Assistance Program.
- Wellness and travel reimbursement.
- Travel discounts and International Airlines Travel Agent Network membership.
- The role is based in Seattle, with compensation and starting pay varying by location, budget, and individual qualifications.
Categories
About Expedia
Expedia Group builds a global online travel marketplace where consumers book flights, hotels, vacation rentals, cars, and activities, and partners distribute and market inventory across its platform. It monetizes through commissions, merchant/agency models, and advertising via brands including Expedia, Hotels.com, and Vrbo. Founded in 1996 and headquartered in Seattle, the public company (NASDAQ: EXPE) serves travelers and partners in more than 70 countries with B2C, B2B, and ad tech offerings.