Machine Learning Engineer III

Expedia•San Jose, CA

69d•$146,000 - $220,500•Hybrid

About The Position

Expedia Group is seeking a Machine Learning Engineer III to join their Advertising Technology team. This role involves building and operating large-scale batch and real-time ML systems for pricing, inventory optimization, ranking, and trust & safety within the ad platform. The position is at the intersection of machine learning, distributed systems, and MLOps, influencing the design, deployment, and operation of production ML systems. The engineer will collaborate with Software Engineering, Data Science, Product, and Platform teams to translate modeling ideas into reliable, observable, and scalable ML systems, while also setting technical direction, raising engineering standards, and mentoring others.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related quantitative field
4+ years of industry experience working with machine learning or data-driven systems
Proficiency in Python and familiarity with ML frameworks such as PyTorch or TensorFlow
Solid understanding of machine learning fundamentals, including supervised learning, feature engineering, model evaluation, and basic bias/variance tradeoffs
Experience working with data pipelines and large datasets, using tools such as Spark, SQL, or similar
Familiarity with software engineering fundamentals, including version control, testing, and basic system design
Ability to collaborate effectively and communicate technical concepts clearly

Nice To Haves

Experience contributing to production ML systems, including model training, evaluation, or inference pipelines
Familiarity with distributed data processing (Spark, Databricks) and cloud environments (AWS preferred)
Exposure to MLOps concepts, such as model deployment, monitoring, or retraining workflows
Experience building or experimenting with ranking, prediction, classification, recommendation, or NLP models
Basic familiarity with real-time or near–real-time ML systems
Background or interest in ads, marketplaces, e-commerce, or travel platforms

Responsibilities

Design and implement scalable batch and real-time ML pipelines to support advertising delivery and optimization across channels.
Operationalize ML models developed by ML scientists, integrating them with ad delivery, bidding, ranking, and campaign management systems.
Build and maintain reliable data pipelines to ingest, process, and transform large-scale ad impressions, clicks, and conversion data.
Partner closely with ads product, engineering, analytics, and business teams to align ML solutions with marketplace and revenue goals.
Enable low-latency inference and real-time decisioning for advertising systems serving millions of users across multiple brands and surfaces.
Develop reusable components, APIs, and orchestration workflows to support experimentation, deployment, and rapid iteration in ad systems.
Ensure reliability, scalability, and performance of ML-powered ad systems through robust monitoring, alerting, and continuous optimization.