.png){kind=logo}
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.
Introduction to the team
The EG Advertising Platform Machine Learning Engineering team builds and operates the ML systems behind TravelAds, Expedia Group’s performance advertising marketplace generating over $1.3B in annual revenue. Our ML Orchestrator processes ~128 million requests per day at 99.9% availability with 25–45ms latency, ranking and scoring ads across multiple traveler experiences. We are transforming how ML models move from idea to production by automating the end-to-end lifecycle — from training and validation to deployment and monitoring — and by building agentic AI workflows that accelerate experimentation and unlock new advertising capabilities.
If you are excited about designing ML systems that automate the entire ML lifecycle while shipping LLM-powered solutions for ad relevance, golden dataset generation, and live inference at scale, this role is for you. This is a team where you won’t just deploy models — you’ll reshape how an advertising ML platform operates at scale.
In this role, you will:
Design and own high-throughput, low-latency ML systems (2000+ RPS) for TravelAds, including multi-service training and serving architectures, auction and ranking models, and real-time inference services that meet strict sub-100ms SLAs.
Build and evolve ML infrastructure and data foundations – feature stores, online/offline feature pipelines, embedding and vector services, and data lineage and versioning – that power ad relevance, bidding optimization, experimentation, and model evaluation at scale.
Accelerate the end-to-end ML lifecycle by automating training, validation, deployment, shadow testing, A/B testing, and retraining using orchestrated workflows (e.g., Flyte, Airflow) and robust quality gates.
Develop agentic AI and LLM/RAG-powered workflows that automate ML operations (training, deployment, validation, monitoring, calibration) and enable AI-assisted dataset creation, operational analysis, and decision support.
Define and implement ML observability, reliability, and cost guardrails through drift and feature-freshness monitoring, health dashboards, SLO/SLI definitions, incident response, and resilience-focused improvements.
Safely integrates and operates AI/ML-enabled solutions that improve outcomes, while setting technical direction, mentoring MLEs to operate independently, and leading cross-team initiatives that elevate ML engineering practices and business impact.
Minimum Qualifications:
Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
8+ years of relevant professional experience.
Proven track record of designing, building, and operating production ML or large-scale distributed systems, including system design (HLD/LLD), serving stacks, monitoring and observability, rollbacks, and operational rigor.
Strong software engineering foundation in Python and at least one of Java/Kotlin/Scala, with deep understanding of distributed systems, data structures, and performance optimization.
Experience leading technical design for multi-quarter ML projects and partnering with Product and business stakeholders to define problems, make clear trade-offs, and measure the business impact of ML systems.
Preferred Qualifications:
Experience with real-time ML inference at high throughput (1000+ RPS or more) and strict latency SLAs.
Expertise with big data technologies such as Spark, Hive, Databricks and workflow orchestration tools such as Airflow and Flyte, as well as cloud-native ML platforms and infrastructure (e.g., AWS SageMaker, EKS, EMR, Docker).
Experience building ML lifecycle automation – CI/CD for ML, automated training pipelines, deployment orchestration, and robust data lineage and versioning – plus ML observability systems including drift detection, feature-freshness monitoring, model health dashboards, and offline/online parity validation.
Track record of leading incident response and root cause analysis for ML or other mission-critical services, and driving sustained improvements in reliability, resilience, and operational excellence.
Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to improve real-world products and engineering outcomes, including experience with LLM productionization, RAG architectures, or agentic AI workflows in high-scale environments.
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, religion, gender, sexual orientation, national origin, disability or age.Skills Required
- Bachelor's degree in Computer Science or related field or equivalent experience
- 8+ years of relevant professional experience
- Proven track record designing, building, and operating production ML or large-scale distributed systems (HLD/LLD, serving stacks, monitoring, rollbacks)
- Strong software engineering foundation in Python and at least one of Java, Kotlin, or Scala
- Experience leading technical design for multi-quarter ML projects and partnering with Product and business stakeholders
- Experience with real-time ML inference at high throughput and strict latency SLAs
- Familiarity with big data technologies (Spark, Hive, Databricks) and workflow orchestration tools (Airflow, Flyte); cloud-native ML infra (SageMaker, EKS, EMR) and Docker
- Experience building ML lifecycle automation (CI/CD for ML, automated training/deployment pipelines), data lineage/versioning, and ML observability systems
- Track record leading incident response, root cause analysis, and driving reliability and resilience improvements for mission-critical services
- Familiarity with LLM productionization, RAG architectures, agentic AI workflows, and AI-driven tooling for ML operations
What the Team is Saying
Expedia Group Compensation & Benefits Highlights
-
Wellbeing & Lifestyle Benefits — Travel and wellness stipends, employee travel discounts, and access to industry credentials create distinctive lifestyle value aligned with the company’s mission. Feedback suggests these perks are widely valued and complemented by programs like charitable matching and volunteer time.
-
Parental & Family Support — Paid parental leave for all parents, additional time for birthing parents, caregiving leave, and fertility/family‑building support indicate comprehensive family backing. Immediate eligibility and flexible return‑to‑work options further strengthen this area.
-
Healthcare Strength — Employer‑provided medical options are positioned as locally competitive and are supplemented by mental‑health platforms and neurodiversity coaching. Health coverage is regarded positively, with multiple support pathways beyond standard insurance.
Expedia Group Insights
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.
Gallery
.jpg)
.jpg)
Expedia Group Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
