Interested in this AI/ML Engineer role at Hilton?
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Exceptional Hospitality Starts with You
This role is based at one of our corporate offices in Dallas, TX or McLean, VA
This is your chance to be part of a Marketing team that attracts customers to Hilton through strong storytelling, top-rated rewards, and unique customer experiences and partnerships. Hilton is building an AI-enabled, data-driven growth engine that creates more relevant guest and member experiences, accelerates direct digital growth, strengthens loyalty engagement, improves marketing effectiveness, and increases the value of every customer interaction. The Senior Director, Marketing Technology Strategy & AI Transformation will lead this evolution across Marketing contributing to Hilton's global portfolio of brands, regions, channels, and customer experiences.
As a Senior Director, MarTech Strategy and AI Transformation, you will support the team in increasing customer acquisition and retention, generate engagement through multi-channel marketing campaigns, and foster recognition of loyalty benefits. On the MarTech team reporting to the Vice President, Marketing Technology & Enablement, you will own the enterprise MarTech product portfolio. The portfolio spans customer data, identity, consent, CRM, lifecycle marketing, journey orchestration, personalization, media activation, content operations, analytics, experimentation, and AI-enabled decisioning. You will lead the development of Hilton's multi-year MarTech strategy, target-state capability architecture, modernization roadmap, and AI transformation agenda. Working across Marketing, Loyalty, Technology, Data, Commercial Services, Finance, Legal, and Privacy teams, you will ensure Hilton's technology investments drive measurable business value, operational efficiency, guest engagement, and sustainable competitive advantage.
What you'll do during a typical day:
- Own Hilton's annual and multi-year MarTech strategy, target-state capability architecture, product portfolio, and investment roadmap.
- Translate business priorities—including direct digital growth, loyalty engagement, guest experience, media efficiency, and customer lifetime value—into scalable technology capabilities and measurable outcomes.
- Lead transformation initiatives spanning platform modernization, consolidation, migration, integration simplification, technical debt reduction and operating model evolution.
- Build investment cases and executive recommendations that balance growth, customer experience, speed to market, adoption, reliability, risk, compliance, and financial value.
- Define and lead a portfolio of AI-enabled MarTech capabilities from opportunity identification through production deployment, adoption and business value realization.
- Evaluate where AI assistants, agents, and orchestration can improve campaign planning, audience creation, journey design, activation, measurement, and marketer productivity.
- Partner with Data Science, Engineering, Analytics, Marketing, and external providers to balance model quality, business impact, latency, cost, reliability, and operational complexity.
- Establish practical standards for AI evaluation, monitoring, human oversight, explainability, fallback processes, access controls, and responsible use.
- Guide product leaders and cross-functional Marketing teams from opportunity framing through delivery readiness, adoption, measurement, and continuous improvement.
- Understand how supported MarTech platforms, integrations, data flows, and dependencies connect to Hilton-wide customer and commercial experiences.
- Use experience, logic, research, and data to assess competing solutions, identify strengths and weaknesses, and recommend differentiated product approaches.
- Develop a strong understanding of competitor and adjacent-industry capabilities through research, conferences, networking, vendor engagement, and reading.
Understand marketing drivers, including campaign lifecycles, media optimization, channel strategy, engagement strategy, and digital marketing. *
How you'll collaborate with others:
- Serve as the senior strategic partner to Marketing, Loyalty, Technology, Data, and Commercial leadership teams.
- Align MarTech investments with enterprise business goals, growth priorities, guest experience objectives, and organizational transformation initiatives.
- Partner with Technology leadership to define future-state architectures, delivery strategies, and modernization approaches.
- Represent MarTech in enterprise-wide initiatives involving customer data, identity, consent, CRM, lifecycle marketing, journey orchestration, personalization, media activation, content operations, analytics, experimentation, and AI-enabled decisioning.
- Engage vendors and strategic partners to assess emerging capabilities, influence product roadmaps, and identify opportunities for innovation and simplification.
- Communicate technology strategy, transformation progress, investment recommendations, and business outcomes to executive leadership.
Build and develop a high-performing team of MarTech product and transformation leaders while fostering a culture of innovation, accountability, and continuous improvement. *
Deliverables you'll take ownership of:
- A current-state assessment and target-state MarTech and AI capability architecture.
- A modernization and simplification plan covering platform consolidation, migration, deprecation, integration, and technical debt.
- Priority AI-enabled marketing capabilities in production, supported by adoption plans, measurement frameworks, and appropriate governance.
- Annual and multi-year MarTech product strategy and capability roadmap, including roadmap narratives, prioritization logic, dependencies, investment tradeoffs, and measurable outcomes.
- Business cases, product investment recommendations and strategy product direction that enable delivery teams to execute effectively.
- Executive-ready communications, including roadmap updates, investment and tradeoff recommendations, risk summaries, launch readiness updates, and post-launch measurement.
What It Takes to Make the Stay
You have these minimum qualifications:
- At least ten (10) years of professional work experience.
- Eight plus (8+) years of experience in hospitality/travel, information systems, product management, marketing, digital technology, AI implementation, or a related field.
- Five (5) years of experience leading cross-functional projects, product roadmaps, or strategic business initiatives at a global or enterprise level.
- Five (5) years of experience in product management, product strategy, business capability development, or digital platform delivery.
- Five (5) years of experience leading teams.
- Experience leading large scale MarTech modernization initiatives
Experience deploying AI-enabled capabilities into production environments *
It would be useful if you have:
- BA/BS Bachelor's Degree in Information Systems, Marketing, Hospitality, Business, or a related field.
- Sixteen (16) years of work experience in any relatable field.
- Five (5) years in product management, consulting, marketing technology, digital marketing, loyalty, data, or IT-related field.
- Experience with marketing technology platforms, customer data platforms, loyalty platforms, campaign activation tools, personalization, decisioning, or digital customer experience ecosystems.
- Project Portfolio Management (PPM), Agile development, product operating model, or scaled delivery knowledge.
Vendor management experience, including roadmap alignment, capability assessment, contract inputs, and performance management. *
How We'll Help You Thrive
At Hilton, the hospitality we're known for doesn't end with our guests. We proudly invest in our Team Members' wellbeing, supporting you through all of life's moments. When you join Hilton, our exceptional care extends to you with unmatched perks and benefits, including*:
- Incredible travel perks – Enjoy 110 nights of deeply discounted travel, with room rates as low as $40/night at our world-class hotels through our Go Hilton travel program
- Own a piece of Hilton – Through our employee stock purchase program (ESPP), you can invest in Hilton shares at a 15% discount to help build your financial future
- Paid parental leave – Because family matters. We offer paid leave for eligible Team Members, including partners and adoptive parents
- Personalized caregiving support – Access dedicated caregiving concierge services to help navigate caregiving for yourself and your loved ones
- Crisis concierge – In times of loss, our Crisis Concierge offers a single, compassionate point of contact for both practical support and emotional care
- Mental health resources – Your wellbeing comes first. Eligible Team Members can access free counseling and support through our best-in-class Employee Assistance Program (EAP)
- Generous paid time off (PTO) – Recharge, relax, and take time for what matters most
- Health & welfare benefits – From checkups to dental cleanings to new glasses, we offer a variety of health plans that keep you and your family covered
- Financial security for your future – Our retirement plans make it easier to save for what's next
*Benefits availability may vary depending on Team Member's location as well as terms and conditions of employment and are subject to the terms and conditions of each specific program/plan.
Hilton offers its eligible team members a comprehensive benefits package to support their mental and physical well-being, so they can Thrive personally and professionally. The pay range for this role is $175,000 – $230,000 and is determined based on applicable and specialized experience and location. Subject to plan terms and conditions, you will be eligible to participate in the Hilton Annual Incentive (Bonus) Plan, and the Company's long-term incentive plan, consistent with other team members at the same level and/or position within the Company.
Join an Award-Winning Workplace Culture
At Hilton, we don’t just deliver exceptional experiences for our guests—we build an exceptional workplace for the Team Members who make it all possible. As a global leader in hospitality, we’ve welcomed more than 3 billion guests worldwide, all while staying true to our founding vision: to fill the earth with the light and warmth of hospitality. Our award-winning culture has earned us repeated recognition on the World’s Best Workplaces list by Great Place to Work and Fortune. With our suite of world-class brands , and a company-wide commitment to providing the best stay for every guest, we’re setting new standards for the future of travel. Whether you’re starting your career or exploring something new, Hilton supports your journey every step of the way. Come for the job, stay for the career—and help us make every stay a little more magical. Curious about life at Hilton? Explore our Careers Blog to see why we’re more than a great place to stay—we’re a great place to work.
Salary Context
This $175K-$230K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Hilton, 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 11,866 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. Disclosed range: $175K to $230K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
Hilton AI Hiring
Hilton has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in McLean, VA, US. Compensation range: $230K - $230K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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