Machine Learning Scientist III

Overview

As a member of the Content AI team, you apply machine learning to improve content quality and relevance for travelers. You will translate research into scalable production ML solutions, collaborating with cross-functional partners to solve complex problems. You’ll design end-to-end ML pipelines, deploy models, and monitor performance to drive business impact. This role sits at the intersection of data science, software engineering, and product, shaping how content is understood and recommended across Expedia Group. You will work in a fast-paced, AI-driven environment that values experimentation and clear technical leadership.

Responsibilities

• Develop, evaluate, and improve ML models for Content AI applications.
• Design end-to-end ML solutions covering data prep, feature engineering, training, deployment, and monitoring.
• Apply statistical analysis and experiments to guide technical direction and measure model performance.
• Collaborate with engineers, PMs, scientists, and domain experts to translate business problems into scalable ML solutions.
• Contribute to system design, API development, and data modelling for production ML systems.
• Build and operate production ML solutions using Python, TensorFlow, PyTorch, Redis, Airflow, Docker, Kubernetes, and cloud-native infrastructure.
• Design and deploy scalable batch and real-time ML pipelines for customer-facing apps.
• Develop and operationalize LLM, RAG, and Generative AI capabilities for content understanding and recommendations.
• Create evaluation frameworks and observability to monitor quality, reliability, latency, drift, and business impact.
• Weigh trade-offs between model quality, scalability, latency, and cost in product development.
• Partner with engineering teams to deploy and scale ML systems in production.
• Produce technical documentation and share expertise through reviews and mentorship.

Key requirements

• Bachelor’s degree in Computer Science, ML/AI, Engineering, Data Science, or related field; or equivalent experience
• 5+ years of production ML development experience
• Strong Python programming and production services/API development
• Experience with TensorFlow and/or PyTorch
• Experience with end-to-end ML lifecycle: experimentation, evaluation, deployment, monitoring
• Experience building/operating production ML systems at scale
• Understanding of distributed systems, data structures, algorithms, system and API design, data modelling
• Experience with batch and real-time data processing and low-latency tech like Redis, KServe, FastAPI
• Ability to collaborate with cross-functional teams to deliver measurable ML outcomes

• collaboration
• problem-solving
• data-driven decision making
• Python
• TensorFlow
• PyTorch

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