Senior ML Platform Engineer - Scale, Observe, Deliver

Expedia, Inc.; Seattle, Northern (WA, KY); Hybrid; USD 185,000 - 258,000; Full time

Benefits offered by this job

Health/Dental/Vision

Paid time off

Employee Assistance Program

Wellness & travel reimbursement

Travel discounts

IATAN membership

Job summary

Expedia Group is seeking a Senior Software Development Engineer for the ML Platform in Seattle. You will design and evolve scalable ML platform capabilities, enabling feature engineering, model inference, and observability across domains.

You will deliver high-quality software, improve production reliability, and partner with teams to adopt shared ML infrastructure while balancing near-term delivery with long-term scalability.

Qualifications

• Bachelor's degree in CS or related field, or equivalent experience.
• 8+ years of professional software experience.
• Ownership of multi-service components with end-to-end accountability.
• Strong fundamentals in system design, coding, testing, and performance.
• Experience with ML platforms or data-intensive infra.

Responsibilities

• Design and evolve scalable ML platform capabilities.
• Deliver high-quality software with engineering best practices.
• Improve reliability, performance, and operational health in production.
• Collaborate with engineers and stakeholders to define approaches.
• Apply technical judgment for scalability and maintainability.
• Safely integrate AI/ML-enabled solutions into products.

Skills

System design

Code performance

ML platforms

Observability

Reliability engineering

Cross-functional collaboration

Education

Bachelor's in CS

Tools

Python

Java/Scala

TensorFlow

Kubernetes

Job description

Expedia Group is seeking a Senior Software Development Engineer for the ML Platform in Seattle. You will design and evolve scalable ML platform capabilities, enabling feature engineering, model inference, and observability across domains.

You will deliver high-quality software, improve production reliability, and partner with teams to adopt shared ML infrastructure while balancing near-term delivery with long-term scalability.