Interested in this AI/ML Engineer role at Capstone Transportation?
Apply Now →About This Role
LEAD THE FUTURE OF HEALTHCARE – CEO In Training Opportunity
Are you a natural leader with an entrepreneurial spirit, ready to take the next step in your career? Capstone Transportation, a Connect Health affiliate, we’re not just offering a job—we’re inviting you to lead a healthcare operation that transforms lives. Through our CEO in Training (CIT) program, you’ll gain hands-on operational experience, personalized mentorship from seasoned executives, and the strategic foundation needed to grow into an Executive Director — and a CEO — within one of our fast-growing Capstone affiliates in the non-emergency and emergency medical transportation sector. This full-time, paid program role (approximately 6–8 months) is built for high-potential leaders who are eager to learn, take ownership, and lead with purpose.
If you're ready to be part of a mission-driven team and shape the future of healthcare—this is your moment.
What we're looking:
*Leadership & Experience*
· 2–3 years of proven leadership with strong results (required)
· Bachelor’s degree (preferred)
· Healthcare experience is a plus, but not required
*Skills & Strengths*
· Strong financial management and business acumen
· Excellent leadership and team-building skills
· Effective multitasking and prioritization
· Sharp problem-solving and decision-making abilities
· Experience in staff training and development
*Communication & Culture*
· Clear, confident communicator with public relations skills
· Strong interpersonal skills and emotional intelligence
· High ethical standards and commitment to quality care
· Thrives in fast-paced environments
· Organized, reliable, and values-driven
What You’ll Experience:
From day one, you’ll be trained, coached, and mentored on how to lead a high-performing Capstone operation. This isn’t a passive learning experience—it’s an immersive pathway designed to prepare you for leadership. You’ll gain hands-on exposure to every facet of the business: financial management, clinical operations, team leadership, and strategic growth. You’ll shadow seasoned leaders, execute real initiatives, and make decisions that matter. All while being guided by experienced operators who are currently running their own successful operation.
Think of it as a startup incubator for future healthcare CEOs—where you’ll learn by doing, grow through mentorship, and build something that truly makes a difference.
What Awaits You After the Program:
Upon successful completion, you’ll step into a CEO/Executive Director role—owning the vision, direction, and operational control of your own healthcare company. You’ll have the autonomy to lead, grow, and innovate—supported by Connect Health’s world-class service center in HR, finance, clinical, IT, and more.
About Capstone:
Capstone Transportation provides compassionate non-emergency and emergency medical transport, ensuring individuals can safely access the care they need. Since 2015, our independent operating affiliates have supported communities with a full range of services, including ambulatory transport, advanced medical transport, long-distance transfers, behavioral health transportation, and air-medical coordination.
Our mission is to dignify and transform the medical transportation experience. We empower local leaders through an entrepreneurial, field-driven culture that keeps decision-making close to the communities we serve. Guided by our core values — celebration, accountability, passion for learning, love one another, intelligent risk-taking, customer second, and ownership — we focus on delivering high-quality, reliable, and cost-effective solutions.
As we expand into new markets, we remain committed to innovation, strong healthcare partnerships, and developing future leaders who will carry our mission forward.
Job Type: Full-time
Pay: From $45,000.00 per year
Benefits:
- 401(k)
- Dental insurance
- Employee discount
- Health insurance
- Paid time off
- Vision insurance
Application Question(s):
- This position may require relocation. Are you open to relocating anywhere in the United States if selected for this opportunity?
Education:
- Bachelor's (Preferred)
Experience:
- Leadership: 3 years (Preferred)
- Healthcare: 1 year (Preferred)
Work Location: In person
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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Capstone Transportation, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Capstone Transportation AI Hiring
Capstone Transportation has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Carrollton, TX, US, Boise, ID, US, Salt Lake City, UT, US.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $145,600. 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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.