Machine Learning Engineer III

Posted 2 Hours Ago
Be an Early Applicant
San Jose, CA, USA
Hybrid
146K-252K Annually
Mid level
AdTech • eCommerce • Information Technology • Software • Travel • Generative AI
Helping travelers explore the world. One journey at a time.
The Role
Design and operate scalable batch and real-time machine learning pipelines for advertising systems. Deploy and integrate models into ad delivery, bidding, ranking, and campaign platforms; build large-scale data pipelines; enable low-latency inference; develop reusable tooling and orchestration workflows; and monitor system reliability and performance. Collaborate with engineering, data science, product, analytics, and business teams while contributing to technical direction and mentoring.
Summary Generated by Built In

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.


Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

About the Team:

We are seeking a Machine Learning Engineer II to join our Advertising Technology team, where we build and operate large-scale batch and real-time ML systems that power pricing, inventory optimization, ranking, and trust & safety across the ad platform. This role sits at the intersection of machine learning, distributed systems, and MLOps, directly influencing how models are designed, deployed, and operated in production at scale.

You will work closely with Software Engineering, Data Science, Product, and Platform teams to translate modeling ideas into reliable, observable, and scalable ML systems, while setting technical direction, raising engineering standards, and mentoring others as the platform and business grow.

In this role, you will:

  • ML Infrastructure & Pipelines: Design and implement scalable batch and real-time ML pipelines to support advertising delivery and optimization across channels

  • Model Deployment & Integration: Operationalize ML models developed by ML scientists, integrating them with ad delivery, bidding, ranking, and campaign management systems

  • Data Engineering: Build and maintain reliable data pipelines to ingest, process, and transform large-scale ad impressions, clicks, and conversion data

  • Cross-Functional Collaboration: Partner closely with ads product, engineering, analytics, and business teams to align ML solutions with marketplace and revenue goals

  • Advertising at Scale: Enable low-latency inference and real-time decisioning for advertising systems serving millions of users across multiple brands and surfaces

  • Tooling & Automation: Develop reusable components, APIs, and orchestration workflows to support experimentation, deployment, and rapid iteration in ad systems

  • Monitoring & Optimization: Ensure reliability, scalability, and performance of ML-powered ad systems through robust monitoring, alerting, and continuous optimization

Minimum Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related quantitative field

  • 3 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

Preferred Qualifications

  • 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

Please note that this role is only available in San Jose, CA or Seattle, WA, in alignment with our flexible work model, which requires employees to be in the office at least three days a week. We are unable to offer relocation assistance for this role.

The total cash range for this position in San Jose is $157,500.00 to $220,500.00. Employees in this role have the potential to increase their pay up to $252,000.00, 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 $146,000.00 to $204,500.00. Employees in this role have the potential to increase their pay up to $233,500.00, 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.


Benefits and perks

Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life.


Accommodation requests

Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation.


About Expedia Group

Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease.


Important notice

Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/.


Equal Opportunity

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, veteran status, or any other characteristic protected by law. 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.

Skills Required

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field
  • 3+ years of industry experience working with machine learning or data-driven systems
  • Proficiency in Python and familiarity with machine learning frameworks such as PyTorch or TensorFlow
  • Understanding of supervised learning, feature engineering, model evaluation, and basic bias/variance tradeoffs
  • Experience with data pipelines and large datasets using Spark, SQL, or similar tools
  • Familiarity with software engineering fundamentals, including version control, testing, and basic system design
  • Ability to collaborate effectively and communicate technical concepts clearly
  • Experience contributing to production machine learning systems, including training, evaluation, or inference pipelines
  • Familiarity with distributed data processing using Spark or Databricks and cloud environments, preferably AWS
  • 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 machine learning systems
  • Background or interest in advertising, marketplaces, e-commerce, or travel platforms

What the Team is Saying

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The Company
HQ: Seattle, WA
16,000 Employees
Year Founded: 1996

What We Do

Expedia Group, Inc. is the global travel marketplace with one purpose: to help travelers explore the world, one journey at a time. Expedia Group™ connects travelers, partners, and advertisers through its trusted brands, leading technology, and rich first-party data, delivering predictive, personalized experiences that shape the future of travel. Expedia Group’s ecosystem includes three flagship consumer brands – Expedia®, Hotels.com®, and Vrbo® – the largest B2B travel business, and a premier advertising network. Guided by an experienced and passionate global team, Expedia Group helps millions of travelers in more than 70 countries explore the world with confidence and ease.

Why Work With Us

Life at Expedia Group starts with the people and is shaped by how we work together. You’ll join a global community of curious teammates from different backgrounds, locations, and disciplines. Day to day, that means sharing ideas, taking ownership, and solving problems together.

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Expedia Group Offices

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Employees engage in a combination of remote and on-site work.

Typical time on-site: 3 days a week
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