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Machine Learning Engineer III - Job Opportunity at Expedia Group

Seattle, United States
Full-time
Senior
Posted: May 11, 2025
Hybrid
USD 137,500 - 192,500 per year

Benefits

Comprehensive travel perks for global exploration
Flexible and generous time-off policy
Parental leave with full support
Flexible work model with hybrid office options
Career development resources and learning opportunities
Competitive health and wellness package

Key Responsibilities

Lead productionization and maintenance of large-scale ML pipelines in AWS
Architect and implement solutions for batch and real-time data processing
Drive technical evaluation and integration of emerging ML technologies
Design and optimize data structures and pipelines for machine learning operations
Coordinate cross-functional collaboration for ML platform development
Develop automated workflows for bidding operations and campaign management

Requirements

Education

Bachelor's, Master's, or Technical degree

Experience

5+ years of relevant experience

Required Skills

Python scikit-learn/Tensorflow/PyTorch OOAD Design patterns SQL and NoSQL Cloud infrastructure Big Data applications (Hive, ElasticSearch, PostgreSQL, DataBricks, Kedro, Dremio, Tableau) Machine learning pipelines Agile development Version control
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Sauge AI Market Intelligence

Industry Trends

Travel industry's increasing investment in ML automation and personalization is driving demand for sophisticated bidding and pricing systems Growing emphasis on real-time processing capabilities for dynamic travel marketplace operations Shift towards cloud-native ML architectures for scalable travel technology platforms

Salary Evaluation

The offered salary range of USD 137,500 - 192,500 is competitive for a senior ML engineer in Seattle, with potential for growth to USD 220,000 based on performance. This aligns with market rates for similar roles at major tech companies.

Role Significance

Part of a distributed team across London and Seattle, typically consisting of 8-12 engineers with varying specializations
Senior-level position with significant technical leadership responsibilities and direct impact on core business operations

Key Projects

Automated bidding optimization systems Real-time pricing engine development ML pipeline automation and scaling Cross-brand marketing strategy implementation

Success Factors

Deep understanding of ML operations and production environments Ability to bridge data science and engineering practices Strong system design and optimization skills Experience with high-volume data processing Collaborative approach to cross-functional development

Market Demand

Very high demand, particularly in the travel sector's digital transformation initiatives. ML Engineers with experience in large-scale systems are increasingly crucial for travel platforms' competitive advantage.

Important Skills

Critical Skills

Production ML pipeline expertise - Essential for maintaining and scaling automated systems Cloud infrastructure knowledge - Critical for distributed system architecture Python and ML frameworks - Core to development and implementation

Beneficial Skills

Travel industry domain knowledge Distributed systems expertise Marketing technology experience Performance optimization skills

Unique Aspects

Opportunity to work on ML systems affecting multiple major travel brands
Exposure to high-volume, real-world travel marketplace dynamics
Balance of technical depth and business impact in travel tech

Career Growth

2-4 years typical progression timeline with demonstrated impact and leadership

Potential Next Roles

Principal Machine Learning Engineer Technical Lead - ML Platform ML Architecture Manager Director of Machine Learning

Company Overview

Expedia Group

Expedia Group is a global travel technology leader operating multiple major brands and platforms

Industry leader in online travel services with significant technical infrastructure and innovation capabilities
Major technical hub in Seattle with global reach and distributed teams
Innovation-focused environment with emphasis on technical excellence and work-life balance
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