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About This Role
Company Description
As a leading healthcare education organization, Unitek Learning’s family of schools helps thousands of students launch and accelerate their careers every year. As a rapidly growing and highly successful company, Unitek is also a great place to pursue a rewarding and challenging career. We offer a competitive salary, generous benefits, unlimited growth potential, and a collegiate work environment.
Job Description
The VP of Marketing is responsible for leading a comprehensive marketing strategy and creative vision across Unitek Learning’s colleges in the Mountain West region aligning efforts with the company’s growth goals. Oversee the development of all creative assets, leverages data\-driven insights to drive lead generation, and collaborate with agencies and internal stakeholders to drive results. Provides direction and mentorship to a high\-performing marketing team.
This position is a hybrid role based in Tempe, AZ. You will be required to work Tuesday\- Thursday at our Tempe campus and two days from your home office.
- Develop and implement milestones and performance metrics to track marketing effectiveness, monitor growth, and accurately forecast future trends.
- Develop and execute comprehensive, multi\-channel marketing plans, including digital, social, local events, etc., to drive performance for campuses and programs.
- Collaborate with regional counterpart on marketing strategies, processes and media performance to unify brand messaging and enhance process efficiency across all college locations.
- Establish advanced processes, tools, and methodologies to deliver comprehensive market intelligence and competitive analysis, supporting strategic decision\-making across all mountain west region colleges.
- Collaborate with cross\-functional executives and internal business leaders to ensure marketing initiatives align with organizational goals, delivering measurable business impact.
- Act as a liaison with advertising agencies and external partners, driving seamless brand execution across all media channels. Facilitate collaboration through clear communication, asset sharing, and concept development.
- Oversee the maintenance and ongoing development of digital properties, including brand websites, platforms, and college domain management.
- Evaluate and recommend the adoption of emerging digital marketing technologies to enhance brand presence, engagement, and lead generation.
- Manage, prioritize, and approve all creative projects to ensure alignment with strategic goals, operational priorities, and budget constraints.
- Ensure timely execution of projects by maintaining transparent, two\-way communication with stakeholders and delivering professional, compelling presentations that reflect Unitek Learning’s brand values.
- Allocate resources and manage the marketing budget for the mountain west group of colleges.
- Work cross functionally within marketing to execute marketing strategies and campaigns.
- Stay ahead of emerging trends in digital, media, AI, automation, and creative execution to maintain competitive differentiation.
Qualifications
- Bachelor’s Degree
- 10\+ years of related experience
- 5\+ years of direct team leadership with a record of driving growth and performance
- Expertise in Microsoft (Word, Excel, Outlook, PowerPoint) and Adobe Creative Suite (Illustrator, InDesign, Photoshop, Acrobat)
- Demonstrate the ability to lead and execute high\-level marketing strategies across a complex, multi\-brand organization.
- Must have exceptional communication skills with the capacity to influence and collaborate effectively across all levels of leadership.
- A proven ability to develop and articulate strategic vision.
- Build strong cross\-functional partnerships and foster alignment across diverse teams.
Additional Information We Offer:
- Medical, Dental and Vision starting the 1st of the month following 30 days of employment
- 2 Weeks’ starting Vacation per year. Increasing based on years of service with the company
- 12 paid Holidays and 2 Floating Holiday
- 401K with a Company Match
- Company Paid Life Insurance at 1x’s your annual salary
- Leadership development and training for career advancement
- Tuition assistance and Forgiveness for you and your family up to 100%, depending on the program
Salary Context
This $120K-$150K range is above the median 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 Unitek Learning, 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. This role's midpoint ($135K) sits 19% below the category median. Disclosed range: $120K to $150K.
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.
Unitek Learning AI Hiring
Unitek Learning has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Tempe, AZ, US, Concord, CA, US. Compensation range: $110K - $150K.
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
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