Interested in this AI/ML Engineer role at Expedia Group?
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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 flexible work model (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.
Who You Are
You’re a senior content and communications leader with strong editorial instincts, a sharp understanding of the evolving media landscape, and a clear point of view on how AI is reshaping brand discovery, interpretation, and trust. You know how to build content strategies that serve both people and platforms, and you understand that today’s communications function must operate with the speed, rigor, and judgment of a newsroom.
You bring deep expertise in editorial strategy, content development, integrated communications, and storytelling across earned, owned, and shared channels. You’re equal parts strategist and operator: able to identify the stories that matter, build the systems that scale them, and lead high\-quality content production from concept through distribution. You thrive in cross\-functional environments and are passionate about ensuring Expedia Group’s brands show up with clarity, credibility, and consistency across traditional media, social platforms, and AI\-powered search experiences.
What You’ll Do
- Lead Expedia Group’s editorial content strategy, building a high\-impact content engine that supports brand reputation, business priorities, and audience engagement across channels.
- Establish and run a centralized content function that operates like a newsroom – identifying timely story opportunities, setting editorial priorities, and producing high\-quality, insight\-driven content at speed.
- Own the editorial calendar and content development pipeline, ensuring a steady drumbeat of relevant, strategic content that can be adapted across PR, executive communications, social, influencer, web, and internal storytelling needs.
- Develop content designed for discoverability and performance across AI\-powered search environments, traditional search, and emerging platforms – applying best practices in structure, authority, relevance, and amplification.
- Partner closely with PR, social, influencer, brand, regional communications, and business teams to translate company priorities into compelling stories, campaigns, and content packages.
- Create scalable editorial frameworks, workflows, and governance that improve speed, consistency, and quality across content creation and distribution.
- Shape content in formats that meet the moment, from reactive and rapid\-response storytelling to proactive thought leadership, feature storytelling, executive bylines, media\-ready assets, and platform\-native content.
- Identify opportunities to strengthen Expedia Group’s visibility and accuracy in AI\-generated search results and summaries by improving content quality, coverage, clarity, and signal distribution.
- Monitor trends in media, AI search, consumer behavior, and platform dynamics to inform editorial decisions and recommend new formats, channels, and approaches.
- Partner with regional communications teams to create globally aligned content that can be efficiently localized for key markets without losing strategic consistency or editorial quality.
- Use data and performance insights to refine strategy, optimize output, and measure the impact of content on visibility, engagement, reputation, and share of conversation.
- Support issues and crisis response with clear, credible, rapid\-turn content that helps protect brand trust and ensure accurate representation across media and AI surfaces.
What You Bring
- 8\+ years of experience in content strategy, editorial, communications, public relations, journalism, or a related field.
- Significant experience leading content development in a fast\-paced, high\-visibility environment, with a strong track record of building editorial programs that drive measurable impact.
- Strong understanding of how AI\-powered search, large language models, and evolving search behaviors are influencing brand visibility, authority, and trust.
- Experience operating a centralized content model or editorial hub, including planning, prioritization, production workflows, and cross\-functional governance.
- Excellent editorial judgment and storytelling skills, with the ability to translate complex business topics into clear, compelling, audience\-first content.
- Experience creating content for multiple channels and audiences, with an understanding of how to adapt stories for PR, social, executive, web, and influencer use.
- Familiarity with SEO fundamentals and emerging approaches to AI search optimization, including content structure, source credibility, and discoverability.
- Strong analytical mindset and comfort using data to evaluate content performance, inform decisions, and continuously improve results.
- Exceptional collaboration and stakeholder management skills, with the ability to influence across functions and lead through ambiguity.
- A proactive, adaptable, and future\-focused mindset, with enthusiasm for innovation and experimentation in a rapidly changing communications environment.
Preferred Qualifications
- Experience in a global consumer brand, technology company, travel brand, media organization, or fast\-moving corporate environment.
- Background in communications, journalism, editorial operations, or content publishing.
- Experience managing agencies, freelancers, or distributed content contributors.
- Familiarity with brand reputation monitoring, media intelligence, and digital performance tools.
The total cash range for this position in Seattle is $155,000\.00 to $217,000\.00\. Employees in this role have the potential to increase their pay up to $248,000\.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.
Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness \& travel reimbursement, travel discounts, and an International Airlines Travel Agent ( IATAN ) membership. View our full list of benefits .
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, 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 $155K-$248K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% 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 in Demand for This Role
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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($201K) sits 11% above the category median. Disclosed range: $155K to $248K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Expedia Group AI Hiring
Expedia Group has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Data Scientist. Positions span Austin, TX, US, Seattle, WA, US. Compensation range: $179K - $318K.
Location Context
AI roles in Seattle pay a median of $227,400 across 1,084 tracked positions. That's 14% above the national median.
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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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