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About This Role
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.
Senior AI Engineer
Introduction to the Team
Expedia Group B2B empowers partners to deliver exceptional traveler and B2B experiences, driving growth for both our partners and the Expedia Group marketplace. We achieve this through competitive supply, a trusted advertising and travel media network, and effective affiliate solutions.
As a member of the B2B Supply Marketing Digital Operations Data team, you will drive strategic AI initiatives and intelligent automation efforts that power insights, personalized experiences, and next\-generation marketing capabilities for our partners. This role sits within the Marketing Technology \& Digital Operations Engineering organization and is responsible for identifying, building, and scaling AI\-powered solutions that improve productivity, automate workflows, unlock insights, and transform how marketing teams work. The ideal candidate combines strong technical expertise with curiosity, experimentation, and a deep understanding of how AI can fundamentally change business processes.
In this role, you will:
- Own and drive the AI Engineering roadmap for Digital Operations, ensuring alignment with business objectives, customer needs, and organizational priorities.
- Lead end\-to\-end delivery of AI products and solutions — from ideation, business case development, and prototyping through production deployment, adoption, and continuous optimization.
- Design, develop, and deploy AI\-enabled applications, copilots, intelligent agents, and workflow automation solutions that improve campaign execution, content creation, reporting, and operational workflows.
- Integrate LLMs, enterprise data platforms, APIs, and marketing technologies to create end\-to\-end AI experiences, including retrieval\-augmented generation (RAG) applications and intelligent knowledge assistants.
- Partner with leaders across Marketing Operations, Web, Paid Media, CRM, Analytics, and Data Engineering to identify opportunities where AI can fundamentally transform workflows and decision\-making.
- Build AI solutions that combine business, operational, and marketing data to generate actionable insights and move teams from reactive reporting toward proactive recommendations and automation.
- Develop reusable frameworks, playbooks, and accelerators that enable rapid experimentation and scaling of AI capabilities across Digital Operations and Marketing teams.
- Lead pilots and proof\-of\-concepts that demonstrate measurable business impact, and drive adoption of AI\-first operating models through best practices and governance frameworks.
- Establish standards for AI development, testing, monitoring, governance, and responsible AI practices, partnering with Data Engineering to ensure trusted data foundations.
- Stay current with advancements in Generative AI, Agentic AI, and intelligent automation, contributing to the long\-term AI roadmap for Marketing Technology and Digital Operations.
Experience and Qualifications
Required:
- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical field; or equivalent related professional experience
- 8\+ years of software engineering, data engineering, or platform engineering experience
- 3\+ years of experience building AI, Generative AI, LLM, automation, or intelligent workflow solutions
- Proficiency in Python and modern software engineering practices
- Strong experience with AI frameworks and platforms such as OpenAI, Anthropic, LangChain, LangGraph, CrewAI, AWS Bedrock, Vertex AI, or similar technologies
- Proficiency with MLOps tools and platforms including AWS SageMaker, Bedrock, MLflow, Weights \& Biases, or Databricks
- Strong knowledge of cloud platforms (AWS preferred) with experience deploying scalable AI services, APIs, and microservices
- Proven track record of operationalizing AI/ML models in production environments with monitoring, observability, and performance optimization
- Experience integrating AI solutions with enterprise applications, APIs, cloud platforms, and data ecosystems
- Proficient communication skills with the ability to work both collaboratively and autonomously across technical and non\-technical teams
Preferred:
- Experience in marketing technology, including familiarity with CRM systems, marketing automation platforms, or personalization engines
- Familiarity with Salesforce, Adobe Experience Cloud, Marketo, Braze, or similar MarTech ecosystems
- Experience building enterprise AI copilots, assistants, or agent\-based automation solutions
- Knowledge of AI governance, responsible AI practices, and enterprise AI adoption strategies
- Experience leading AI transformation initiatives with measurable business outcomes
\#LI\-AD1
The total cash range for this position in Austin is $184,500\.00 to $258,000\.00\. Employees in this role have the potential to increase their pay up to $295,000\.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.\&\#xa;The total cash range for this position in Chicago is $171,500\.00 to $240,000\.00\. Employees in this role have the potential to increase their pay up to $274,500\.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 $184,500\.00 to $258,000\.00\. Employees in this role have the potential to increase their pay up to $295,000\.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.
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.
Salary Context
This $171K-$295K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Expedia Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($233K) sits 9% above the category median. Disclosed range: $171K to $295K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Expedia Group AI Hiring
Expedia Group has 5 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Austin, TX, US, Seattle, WA, US. Compensation range: $186K - $387K.
Location Context
AI roles in Austin pay a median of $214,343 across 143 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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