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Expedia

Machine Learning Engineer III

Seattle, WA Austin, TX
USD 137k - 220k
Python Java AWS Kubernetes Docker Machine Learning Spark Streaming
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Description

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

Introduction to the team 

We're seeking talented machine learning engineers to join our Travel Interactions & Intelligence (TII) team, a core unit that powers critical customer-facing functionalities in our travel platform. We are looking for a top performer who mentors junior engineers, applies new data engineering principles to improve existing systems, and leads complex, well-defined projects.  

The Travel Interactions & Intelligence (TII) team is responsible for two key pillars: 

  • Price Intelligence & Forecasting: design and maintain sophisticated ML systems to predict travel pricing based on historical pricing data 

  • Customer Engagement Systems: implement smart triggers for price alerts, deals suggestions, and travel updates 

 

In this role, you will: 

  • Proactively teams up with peers across the organization to build an understanding of cross dependencies and shared problem solving 

  • Thinks holistically to identify opportunities around policies/ processes to increase efficiency across organizational boundaries 

  • Tests, monitors, debugs, and fixes issues within established SLAs 

  • Has a strong command with Spark and how map-reduce works, how to evaluate, optimize, and debug Spark applications 

  • Is familiar with training models with very large datasets- strategies for parallelizing and optimizing the training jobs especially with GPUs or large-compute 

  • Can instrument streaming and parallel inference tasks to accommodate large traffic or volume of data 

 

Experience and qualifications:  

  • 5+ years for Bachelor's, 3+ years for Master's, or Bachelor's or Master's or equivalent experience. Technical degree preferred 

  • Strong programming skills in Python or Java 

  • Familiar with cloud services (e.g., AWS) and workflow orchestration tools (e.g., Airflow) 

  • Built and maintained at least one machine learning engineering pipeline end-to-end in production environments, including feature engineering, model training, model scoring, model serving (Kubernetes, Docker), etc. 

  • Built and maintained live and streaming applications in a hybrid/cloud infrastructure (Splunk, Datadog) 

  • Built and maintained complex data pipelines for large data processing 

The total cash range for this position in Austin is $137,500 to $192,500. Employees in this role have the potential to increase their pay up to $220,000, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.

Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future.

Accommodation requests

If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
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