Interested in this AI/ML Engineer role at Kampgrounds of America?
Apply Now →Skills & Technologies
About This Role
Kampgrounds of America, Inc. (KOA) is the world’s largest network of privately owned campgrounds and the leader in outdoor hospitality. KOA has 500\+ locations across the United States and Canada including a mix of franchised and company\-owned parks (OAK). Founded in 1962, the mission of KOA is “connecting people to the outdoors and each other,” and those who represent the brand share the values of being family\-oriented, passionate, entrepreneurial, customer\-focused, and innovative.
At KOA, we believe the outdoors is fun and for everyone. We are committed to having an environment where all are treated with dignity and respect. We strive to:
- intentionally create a sense of community and belonging for our guests, employees and franchise partners
- continually educate ourselves and expand our knowledge to foster an inclusive and supportive environment
- sustain a culture that promotes diversity of thought and experiences
- ensure everyone has the ability to experience the outdoors and that our facilities are accessible to all
- drive change in our company and industry through action and implementation
Summary:
The Campground Management Internship Program offers the opportunity for undergraduate students to expand their classroom knowledge by developing skills, habits, and experience in a hands\-on work environment, while enjoying the great outdoors.
The 12\- week internship program serves as a pre\-Manager\-In\-Training program, allowing the participants to focus on campground operations, management, marketing and administration. Interns will train first\-hand by working alongside our experienced managers.
Essential Duties and Responsibilities:
- Spend 12 weeks shadowing and working within the 4 core departments \- operations, management, marketing and administration.
- Duties may include working in all campground positions (guest services, maintenance, groundskeeping, food and beverage, housekeeping and operations).
- Responsible for executing day\-to\-day activities assigned by manager.
- Develop and present a final project at the conclusion of the internship.
- Responsible for participating in all internship components including internship workbook, scheduled shifts \& internship meetings and projects.
Non\-Essential Duties and Responsibilities:
This job description is not intended to cover or contain a comprehensive listing of activities, duties, or responsibilities. Other duties, responsibilities and activities may change or be assigned at any time with or without notice.
Required Education and Experience:
- Student pursuing a degree in Management, Business, Communication, Hospitality Management, Entrepreneurship, Outdoor Recreation, Tourism and Recreation Management or related area of study
- Able to meet deadlines and work with internal team members while maintaining a self\-direct approach to ongoing projects
- Ability to collaborate with a diverse population
- Strong organizational skills and attention to detail
- Must demonstrate excellent customer service.
Preferred Education and Experience:
- Excellent verbal and written communication skills – Bilingual is a plus
Physical Demands and Working Conditions:
- Work is performed in an office environment and requires the ability to operate standard office equipment and keyboard, including lifting and carrying a laptop and other small items up to 20 pounds.
- Prolonged exposure to computer screens and artificial lighting.
- Use of repetitive motion, standing, bending, sitting, lifting, and walking short distances.
- May be expected to drive a vehicle to KOA locations, other locations as directed, and conferences which requires close and distance vision, sitting, seeing and reading signs, traffic signals, other vehicles, etc. Travel occurs in all weather conditions, including extreme heat and cold.
- Frequent in person interaction with KOA employees in various settings, where noise level is typically low to moderate, including office spaces.
- Will experience occasional interruptions and shifting priorities.
- Noise levels may be moderate to loud, especially when operating equipment such as lawn mowers, trimmers, or blowers.
- Must be able to hear instructions and warnings in a noisy environment.
- Frequently lift and/or move up to 50 pounds independently; pushing, pulling, and reaching overhead.
- Occasionally lifting and/or move heavier items with assistance or equipment; dexterity of hands and fingers.
- Potential exposure to dust, pollen, grasses, landscaping, and pool chemicals.
- Maintaining balance while on ladders, working in and around water, on wet surfaces, or on elevated platforms.
KOA does not sponsor Visas
KOA currently does not pay or withhold taxes in the following states:
Alabama Idaho Mississippi Pennsylvania
Alaska Illinois Missouri Rhode Island
Arkansas Iowa Nebraska South Carolina
Delaware Kansas New Hampshire South Dakota
District of Columbia Louisiana North Dakota Vermont
Hawaii Maryland Oklahoma West Virginia
Minnesota Oregon Wisconsin
Kampgrounds Of America, Inc. is an Equal Opportunity Employer and strives to provide an environment where all employees and applicants are treated with respect. The company is committed to fair treatment of all people. This value ensures employees and candidates are treated equally and are protected from discrimination or harassment of any kind. All employment decisions shall be made without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), political affiliation, military service, or other non\-merit\-based factors, or any other protected status.
Salary Context
This $31K-$35K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Kampgrounds of America, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($33K) sits 80% below the category median. Disclosed range: $31K to $35K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Kampgrounds of America AI Hiring
Kampgrounds of America has 7 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Fort Collins, CO, US, NC, US, San Diego, CA, US. Compensation range: $35K - $35K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.