Machine Learning Scientist II

Expedia Group

Machine Learning Scientist II developing cutting-edge agentic AI systems for travel enhancements at Expedia Group. Collaborating with product and engineering teams to create high-quality experiences.

Posted 7/14/2026full-timeSan Jose • California • 🇺🇸 United StatesJuniorMid-Level💰 $122,500 - $171,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying agentic AI systems, integrating large language models with external tools, and defining evaluation frameworks for machine learning systems. Proficient in Python and familiar with state-of-the-art techniques in agentic architectures and prompt engineering.

Highest-signal resume keywords

Agentic AI System DesignPython ProficiencyLLM IntegrationEvaluation Framework DevelopmentPrompt Engineering Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAgentic ArchitecturesMulti-Agent CollaborationTask DecompositionTool-Augmented ReasoningReActReflection LoopsChain-of-Thought PromptingPyTorchTensorFlow

Soft Skills

CollaborationRisk MitigationResearch Synthesis

Tools & Technologies

LangChainLlamaIndexAPIsDatabasesCode Execution Environments

Industry Keywords

AI SystemsEvaluation FrameworksProduction MonitoringBenchmarkingTask Success Measurement

Tech Stack

Tools & technologies

PythonPyTorchReactTensorflow

About the role

Key responsibilities & impact

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 state-of-the-art techniques in agentic architectures, such as ReAct, reflection loops, chain-of-thought prompting, and tool-augmented reasoning
Develop and maintain agent orchestration frameworks, defining how agents decompose tasks, delegate to sub-agents, and handle failure and recovery
Integrate large language models (LLMs) with external tools, APIs, databases, and code execution environments to enable real-world task completion
Define and own evaluation frameworks for agentic systems, measuring task success, reliability, latency, cost, and safety across diverse benchmarks and production scenarios
Collaborate closely with product, engineering, and research teams to translate business requirements into agentic system designs and deliver production-grade solutions
Identify and mitigate risks specific to agentic systems, including prompt injection, unintended actions, hallucination in long-horizon tasks, and unsafe tool use
Stay current with the rapidly evolving agentic AI landscape, synthesizing academic research and industry developments to inform the team's technical direction

Requirements

What you’ll need

PhD, MS, or BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field; or equivalent professional experience
2+ years of related industry experience
Demonstrated experience designing and deploying agentic or multi-step AI systems (e.g., ReAct, tool-calling agents, multi-agent pipelines) in production or research settings
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX); experience with LLM APIs and orchestration libraries (e.g., LangChain, LlamaIndex, or similar)
Experience integrating LLMs with external tools, APIs, and structured data sources for real-world task completion
Understanding of prompt engineering techniques including chain-of-thought, few-shot prompting, and structured output generation
Experience defining and running evaluation frameworks for ML systems, including offline benchmarking and production monitoring

Benefits

Comp & perks

medical, dental, and vision coverage
paid time off
Employee Assistance Program
wellness and travel reimbursement
travel discounts
International Airlines Travel Agent Network (IATAN) membership