Interested in this AI/ML Engineer role at Las Vegas Convention and Visitors Authority?
Apply Now →About This Role
The Role:
Reporting to the SVP, AI \& Enterprise Performance, and under the guidance of the AI Steering Committee, this role will help guide the strategy and roadmap for how the LVCVA’s AI systems are built, run, and connected across the organization. The role will set the technical direction for the stack, turn the department’s priorities into working systems, and serve as the conduit to departments, partnering with their teams to map how work gets done and roll out solutions that improve performance and efficiency. This role will serve as an authority on our AI systems, directing how the work is built, integrated, deployed, and maintained.
What You’ll Do:
*Keep in mind that this list is not all\-inclusive.*
Technology Leadership
- Support the design and execution of the roadmap for the AI stack, evolving it as tools and organizational needs change.
- Define the technical standards and architecture for AI systems and integrations.
- Track the AI landscape and translate it into clear direction for where LVCVA’s AI systems go next.
- Integrate AI tools and platforms into a cohesive stack rather than isolated point solutions
- Manage AI vendor and partner relationships, including scoped project work and flexible engineering and data science capacity.
- Oversee AI contracts, budgets, and token usage across tools, coordinating with Finance and IT as needed.
Cross\-Functional Partnership
- Serve as the primary liaison between the AI function and other departments, moving initiatives from idea to deployment.
- Lead a team of people to drive consistent excellence in the development of AI systems and the delivery of AI integration into departments.
- Map how work moves through each department to identify where tools, automation, or process changes improve performance and efficiency.
- Partner with the AI Steering Committee, IT, Legal, and People \& Culture to review, secure, and roll out AI tools, connectors, and governance guardrails across the organization.
Data Intelligence
- Lead development of the systems that power LVCVA’s data intelligence capabilities.
- Partner with and train research and data teams on AI systems, building and maintaining tools that support their work.
- Monitor deployed agents, automations, and dashboards, maintaining feedback loops with users and refining solutions as systems and needs change.
What We’re Looking For:
- Bachelor’s degree in computer science, engineering, information systems, or a related field; advanced degree is a plus.
- 7\+ years of progressively responsible experience in technology, digital, or operations roles, including leadership of complex cross\-functional initiatives.
- Hands\-on fluency with the current AI landscape and a track record of designing, building, and deploying AI solutions in production, not just evaluating vendors or pilots.
- A track record of setting technical direction for AI and integration initiatives, owning a roadmap from concept through delivery and continuous improvement.
- Strong technical fluency to evaluate tools, scope integrations, and translate business needs into practical system requirements with IT and vendor partners.
- Experience mapping business processes and turning them into clear workflows and automation that improve performance and customer experience.
- Proven ability to manage multiple complex, cross\-functional programs at once and to identify practical solutions when the path forward is not obvious.
- Clear, confident communicator with a track record of working across business units and external partners to deliver integrated solutions and influence decisions at all levels.
- Comfortable in a fast\-changing environment, able to adapt quickly as tools, priorities, and requirements evolve, while providing steady leadership in ambiguity. Ability to travel as needed; familiarity with tourism, convention, or public\-sector governance preferred.
- All LVCVA Ambassadors are expected to demonstrate “Do the Right Thing”, “Vegas for All”, and “Be Extraordinary” by acting with integrity, fostering an inclusive and welcoming environment, and delivering exceptional service in everything they do.
The Las Vegas Convention and Visitors Authority (LVCVA) provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the LVCVA will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at [email protected]
MANAGEMENT\-CLASS BENEFITS
Your total compensation at the Authority includes not only your salary, but also the following benefits. These benefits increase your total compensation from 30 to 40 percent.
NEVADA PERS RETIREMENT PROGRAM* 100% employer paid
- https://www.nvpers.org
NO SOCIAL SECURITY TAXES WITHHELD
INSURANCE \- 100% Employer Paid* Medical/Dental/Vision/Rx (employee and dependents)
- Life Insurance – $15,000 plus an amount equal to your annual base salary up to a max of:
+ $200,000 for Sr. Director and Director
+ $150,000 for Sr. Manager and Manager
- Long\-Term Disability (LTD) Insurance
VOLUNTARY INSURANCE – 100% Employee Paid* Life Insurance
- Supplemental Insurance
- Long\-Term Care Insurance
- Flexible Savings Accounts (FSA \& Dependent Care FSA)
- Pet Insurance
PERSONAL TIME OFF (PTO)
HOLIDAYS* 13 per year, includes birthday
DEFERRED COMPENSATION (IRS section 457\)
ANNUAL MERIT INCREASE – July* Ambassadors are eligible for an increase to base pay based on achievement of performance measures.
ANNUAL PERFORMANCE INCENTIVE* Ambassadors are eligible for a performance bonus based upon achievement of goals and successes.
OTHER* Employee Assistance Program
- Education Assistance
NOTE: Benefits subject to change based on the discretion of management.
Salary Context
This $120K-$150K range is in the lower quartile 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 Las Vegas Convention and Visitors Authority, 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 $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($135K) sits 37% below the category median. Disclosed range: $120K to $150K.
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.
Las Vegas Convention and Visitors Authority AI Hiring
Las Vegas Convention and Visitors Authority has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Las Vegas, NV, US. Compensation range: $150K - $150K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 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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