Machine Learning Engineer II

Expedia Group

Machine Learning Engineer II building batch and real-time advertising ML systems for Expedia Group. Deploying scalable models and pipelines across San Jose or Seattle with hybrid office work.

Posted 8/17/2026full-timeSan Jose • California, Washington • 🇺🇸 United StatesJuniorMid-Level💰 $119,000 - $180,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning pipelines, with a strong foundation in software engineering principles and experience in real-time ML systems. Capable of collaborating across teams to enhance model performance and business outcomes while adhering to responsible AI/ML practices.

Highest-signal resume keywords

Machine Learning EngineeringPython or Java ProficiencyMLOps PracticesDistributed Data ProcessingCloud Platforms (AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning FrameworksData Pipeline DevelopmentAPI DesignModel DeploymentMonitoring and TroubleshootingRanking ModelsPrediction ModelsClassification ModelsRecommendation ModelsNatural Language Processing (NLP)

Soft Skills

CollaborationMentoringTechnical Direction

Tools & Technologies

SparkDatabricksAWS

Industry Keywords

AdvertisingMarketplacesE-commerceTravel Platforms

Tech Stack

Tools & technologies

AWSCloudJavaPythonSpark

About the role

Key responsibilities & impact

Build batch and real-time ML pipelines for ad delivery, ranking, bidding, and optimization
Deploy and integrate ML models into low-latency ad delivery and campaign systems
Develop and maintain data pipelines for large-scale impression, click, and conversion data
Create reusable ML components, APIs, and workflows to support experimentation and iteration
Ensure reliability, scalability, and performance through monitoring and continuous optimization
Analyze data to improve models, features, and business outcomes
Collaborate with product, engineering, and analytics teams to deliver marketplace impact
Apply software engineering best practices and support responsible use of AI/ML
Own and deliver ML components or services within cross-functional teams
Mentor others and help set technical direction and engineering standards

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
2+ years of industry experience in machine learning engineering, including model development and production deployment
Proficiency in Python or Java
Experience using machine learning frameworks
Solid software engineering fundamentals
Proven ability to own and deliver ML components or services within cross-functional teams
Familiarity with real-time or near-real-time ML systems and production operations
Experience operating production ML systems at scale, including monitoring, troubleshooting, and iterative improvement
Familiarity with distributed data processing, including Spark and Databricks
Familiarity with cloud platforms, preferably AWS
Exposure to MLOps practices, including model deployment, monitoring, retraining, and CI/CD for ML
Experience building or experimenting with ranking, prediction, classification, recommendation, or NLP models
Experience designing APIs, data pipelines, and data models for ML-powered applications
Interest or background in advertising, marketplaces, e-commerce, or travel platforms
Awareness of responsible and secure AI/ML practices in production environments
Employees must be able to work in the office at least three days a week
No relocation assistance is available

Benefits

Comp & perks

Medical, dental, and vision coverage
Paid time off
Employee Assistance Program
Wellness reimbursement
Travel reimbursement
Travel discounts
International Airlines Travel Agent Network (IATAN) membership
Flexible work model