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Help Shape What AI Looks Like in Hospitality.
AI is changing how businesses operate. At Crescent Hotels & Resorts, we’re focused on something bigger than simply adopting new technology—we want to put AI to work solving real business problems across our hotels.
We are seeking a Regional Vice President of AI Enablement & Implementation to help turn that vision into reality.
This is an opportunity for a builder.
You’ll work alongside Crescent leaders, hotel operators, ownership partners, and functional experts to identify where AI can create meaningful value—and then help take those ideas from opportunity to solution to implementation to measurable results.
We aren’t looking for someone to simply tell us what AI could do.
We’re looking for someone who can help us make it happen.
What You’ll Build
Imagine helping create AI-enabled solutions that could:
- Give a General Manager a daily “GM Pulse” that brings together revenue, labor, cost, guest satisfaction, and operational signals into one actionable briefing.
- Help a sales team qualify an inbound RFP and develop a tailored group proposal in a fraction of the time.
- Optimize hotel labor schedules against forecasted demand to reduce overtime, overstaffing, and unnecessary contract labor.
- Automate repetitive accounting processes, reconciliations, cash-flow forecasting, and reporting.
- Monitor F&B inventory and purchasing patterns to identify waste and over-ordering.
- Help recruiting teams source, screen, schedule, and communicate with candidates more efficiently.
- Turn financial, STR, guest satisfaction, revenue, and operating data into recurring ownership and investor reporting.
- Make it easier for hotel associates and leaders to find information, make decisions, and spend less time on administrative work.
And those are just the opportunities we see today.
A major part of your role will be helping us discover what we haven’t thought of yet.
What You’ll Do
You’ll help establish and execute the AI roadmap for a designated portfolio of Crescent-managed hotels, identifying the opportunities with the greatest potential business impact.
You’ll work across Operations, Commercial, Revenue Management, Sales, Marketing, Finance, Human Resources, and Technology to understand how work gets done today—and where AI, automation, data, or process redesign can make it better.
You’ll help determine whether the right solution should be built, bought, configured, or integrated, and you’ll lead initiatives beyond the idea stage through implementation, adoption, measurement, and optimization.
You’ll partner closely with Crescent’s technology teams around systems, integrations, data, security, and governance while helping operators translate business challenges into practical AI-enabled solutions.
Most importantly, you’ll make sure the solutions we introduce actually get used.
Because successful AI transformation isn’t measured by how many pilots we launch.
It’s measured by what changes because of them.
Who We’re Looking For
You understand AI—but you think like a business leader.
You naturally start with:
“What problem are we trying to solve?”
Then you determine whether AI, automation, data, process redesign—or some combination—is the right answer.
You’re comfortable discussing strategy with executives one moment and sitting with an operator to understand a manual process the next.
You understand technologies such as generative AI, AI agents, workflow automation, APIs, data integration, and emerging AI platforms, but you don’t believe technology is the objective.
Business impact is.
You know how to build a business case, evaluate technology and vendors, lead cross-functional implementation, drive organizational adoption, and measure ROI.
Hospitality experience would be valuable, but we’re also interested in leaders who have successfully driven AI or digital transformation in other complex, multi-unit businesses.
What Success Looks Like
Your work should ultimately help Crescent and our hotels achieve measurable outcomes:
More revenue.
Better productivity.
Smarter labor deployment.
Faster decision-making.
Less administrative work.
Better guest experiences.
More empowered associates.
And demonstrable ROI from AI investments.
Why Crescent?
At Crescent Hotels & Resorts, hospitality is a people business—and we believe technology should make our people better at what they do, not take away from the human experience that defines great hospitality.
This role offers the opportunity to help shape our approach to AI at an important moment in its evolution.
You won’t be stepping into a mature AI program and maintaining someone else’s roadmap.
You’ll help build it.
If you are energized by the opportunity to turn emerging technology into practical solutions, challenge how work gets done, and help shape the future of AI in hospitality, we’d like to hear from you.
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Crescent Hotels & Resorts, 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 $212,000 based on 11,857 positions with disclosed compensation.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Crescent Hotels & Resorts AI Hiring
Crescent Hotels & Resorts has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Fairfax, VA, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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