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Description
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The Chief Marketing & Enrollment Strategy Officer (CMESO) serves as the institution’s senior leader responsible for integrating marketing excellence with a comprehensive, data-driven enrollment strategy that supports the college’s mission, brand reputation, and long-term sustainability.
This role provides strategic vision and operational oversight for all marketing, communications, recruitment, and enrollment initiatives, ensuring that messaging, outreach, and student engagement efforts are coordinated, targeted, and aligned with institutional priorities.
Specific Duties and Responsibilities
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Strategic Leadership
- Provide executive leadership and strategic direction for the institution’s marketing, communications, and enrollment marketing enterprise, ensuring alignment with enrollment goals, academic priorities, and long-term institutional strategy.
- Establish and monitor enrollment-focused performance metrics and brand objectives, leading and developing a high-performing, multidisciplinary marketing and communications team.
Enrollment Marketing and Growth
- Lead institution-wide enrollment marketing strategy to drive inquiry generation, application growth, and yield through integrated, data-informed recruitment campaigns across all student segments and modalities.
- Partner with Enrollment Management and Academic Leadership to align marketing strategy with enrollment targets, program demand, and market-responsive academic offerings.
Communications and Public Relations
- Oversee all institutional communications and public relations efforts to strengthen brand reputation, ensure message consistency, and elevate the college’s visibility and reputation across key audiences.
- Serve as a senior communications advisor and institutional spokesperson, providing leadership during crisis situations and managing relationships with media and external stakeholders.
Digital Strategy & Web Presence
- Direct the college’s digital marketing and web strategy to ensure the website and digital platforms function as high-impact enrollment, brand, and engagement assets.
- Lead digital innovation through marketing automation, analytics, CRM integration, and content strategy to improve recruitment effectiveness and student engagement.
Budget & Resource Management
- Develop and manage the college’s marketing budget to maximize return on investment and ensure resources are aligned with institutional priorities and enrollment outcomes.
- Oversee external vendors, agencies, and partners to ensure effective execution, accountability, and performance outcomes.
Additional Duties
- Serve as a member of the senior leadership team, contributing to institutional strategy, planning, and decision-making at the executive level.
- Collaborate with department members and/or the Compliance, Assessment, and Research (CAR) team to support planning, assessment, data collection, and reporting of college-wide continuous improvement efforts.
- Perform additional duties as assigned by the President in support of institutional priorities.
OVERALL PURPOSE AND RESPONSIBILITY:
The primary and most important overall responsibility of all employees is to provide service in a pleasant, helpful, and effective manner to our students and other members of the College community.
Minimum Qualifications
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Education Required:
Required: Bachelor’s degree in marketing, communications, business, public
relations, digital media, or a closely related field.
Preferred: Master’s degree in marketing, business administration, data
analytics, public relations, higher education administration, or related discipline.
Experience Required:
- Minimum of 5 years of progressively responsible leadership experience in strategic marketing, enrollment marketing, brand strategy, or integrated communications, preferably in higher education or a complex mission-driven organization.
- Demonstrated track record of successful marketing efforts, including inquiry generation, digital lead strategy, funnel optimization, and lead conversion.
- Experience supervising multidisciplinary teams, managing complex budgets, and implementing enterprise-level marketing technology systems (CRM, analytics platforms, automation tools).
- Successful experience developing high-impact digital strategies, marketing campaigns, and brand initiatives.
Skills/Abilities /Knowledge /Other Requirements
- Deep understanding of enrollment marketing, audience segmentation, and student recruitment behaviors.
- Proven ability to use data, analytics, and market research to set and achieve enrollment goals.
- Expertise in branding, digital advertising, content strategy, and multi-channel communications.
- Strong leadership skills, including talent development, team building, and cross-functional collaboration.
- Demonstrated ability to manage relationships with diverse stakeholders including academic leaders, enrollment teams, community partners, media, and external agencies.
- Mastery of digital platforms: CRM systems, marketing automation, SEO/SEM, social media, web analytics, and content management systems.
- Exceptional verbal and written communication skills, including experience producing high-level messaging for multiple audiences.
- Ability to manage complex projects with competing priorities and tight deadlines.
- High degree of strategic thinking, creativity, analytical rigor, and innovation.
- Commitment to student success, and the mission of a community-focused institution.
Additional Information
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INSTITUTIONAL EFFECTIVENESS:
Collaborates with department members and/or the Compliance, Assessment and Research team to support planning, assessment, data collection and reporting for continuous improvement of the college.
Employee Classification: Executive
Residency Requirement: The New Jersey First Act requires employees of all public institutions of higher education to reside in the State of New Jersey unless otherwise exempted under the law. For more information please click here
Salary Context
This $130K-$145K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Rowan College at Burlington County, 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. C-Level-level AI roles across all categories have a median of $259,000. This role's midpoint ($137K) sits 11% below the category median. Disclosed range: $130K to $145K.
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.
Rowan College at Burlington County AI Hiring
Rowan College at Burlington County has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Mount Laurel, NJ, US. Compensation range: $145K - $145K.
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
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