Senior Machine Learning Scientist - Agentic Experience

Expedia Group•San Jose, CA

3d•$173,000 - $261,500

About The Position

Expedia Group’s Traveler Discovery & Planning team develops AI-driven agentic systems that enhance customer experiences, engagement, and traveler relationships. The role focuses on building foundational systems for intelligent travel assistance and personalized trip planning, with solutions that can affect millions of travelers worldwide. The Senior Machine Learning Scientist designs, builds, and evaluates multi-step agentic AI systems, including agents that plan, use tools, manage memory, and collaborate with other agents. The role researches and implements agentic architectures, develops orchestration frameworks, and integrates large language models with external tools and data sources to complete real-world tasks. It also owns evaluation frameworks for agent performance and safety, collaborates across product, engineering, and research, and helps guide the technical direction of the team. The position includes mentoring junior ML engineers and scientists.

Requirements

At least 8 years of related industry experience.
Demonstrated experience designing and deploying agentic or multi-step AI systems, such as ReAct, tool-calling agents, or multi-agent pipelines, in production or research settings.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience with LLM APIs and orchestration libraries such as LangChain, LlamaIndex, or similar.
Experience integrating LLMs with external tools, APIs, and structured data sources for real-world task completion.
Solid understanding of prompt engineering, including chain-of-thought, few-shot prompting, and structured output generation.
Experience defining and running ML system evaluation frameworks, including offline benchmarking and production monitoring.

Nice To Haves

PhD, MS, or BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field, or equivalent professional experience.
Experience in the travel or e-commerce industry.
Publications in top-tier ML conferences or journals.
Patented inventions, pending or issued.
Contributions to open-source ML projects.
Experience taking models from prototype to production in collaboration with Machine Learning Engineering teams.

Responsibilities

Design, build, and evaluate multi-step agentic AI systems, including autonomous agents capable of planning, tool use, memory management, and multi-agent collaboration.
Research and implement agentic architecture techniques such as ReAct, reflection loops, chain-of-thought prompting, and tool-augmented reasoning.
Develop and maintain agent orchestration frameworks, including task decomposition, delegation to sub-agents, and failure handling and recovery.
Integrate large language models with external tools, APIs, databases, and code execution environments to enable real-world task completion.
Define and own evaluation frameworks measuring task success, reliability, latency, cost, and safety across benchmarks and production scenarios.
Collaborate with product, engineering, and research teams to translate business requirements into agentic system designs and production-grade solutions.
Identify and mitigate agentic-system risks, including prompt injection, unintended actions, hallucinations in long-horizon tasks, and unsafe tool use.
Stay informed about agentic AI research and industry developments and use them to inform the team's technical direction.
Mentor junior ML engineers and scientists in agentic design patterns, LLM best practices, and experimentation methodology.