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Position Summary
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Located 45 minutes from the Nation’s Capital, nestled in a history\-rich community of southern Maryland, The College of Southern Maryland (CSM) is a two\-time Aspen Award\-winning institution (top 15% of Community Colleges) with academic programs in over 100 disciplines. CSM is among America’s top 100 producers of Minority Associate Degrees in twenty categories, according to *Diverse Issues in Higher Education. CSM offers excellent health insurance benefits; State Retirement Pension plan; wellness programs; Code Green early closure Fridays in the summer; college closure for spring break and several major holidays, including the week between Christmas and New Year; and for several days in March for Spring Break. We are an innovative institution committed to student success and well known for our flexibility to meet student and community needs.*
The Executive Director of Advanced and Emerging Technology Services provides visionary leadership for the development, launch, and ongoing management of the institution’s emerging IT technologies and hub for artificial intelligence strategy, innovation, and community engagement. The Executive Director will guide institution\-wide AI adoption and governance across teaching, learning, student success, administrative operations, and workforce development. This role will ensure that AI initiatives align with institutional priorities, maintain ethical and responsible AI practices, and strengthen partnerships with internal and external stakeholders. The incumbent will explore, assess, and launch emerging technologies to support improvements in digital innovation, data reporting and analytics (data lakes/data warehouses), and academic, operational and workforce process improvements. This position collaborates closely with our academic, administrative, enterprise applications, and IT operations teams. Additionally, this position has the potential to provide supervision and guidance to student workers, interns, and an Instructional Specialist position in the future, based on programmatic and organizational needs.
*Reports to: VP and Chief Information Officer (CIO)* The hiring salary for this position will be from the min to mid\-point of the salary range advertised. This position is open until filled.
Specific Duties and Responsibilities
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20% Leadership \& Collaboration* Serve as the primary champion for responsible AI adoption/use and the integration of emerging IT technologies across the institution.
- Provide budget management support for the development and oversight of funding supporting the AI Center.
- Provide leadership/oversight for support positions supporting the AI Center.
- Collaborate/Maintain effective communications with key stakeholders including Division of Learning, IT, Planning, Institutional Effectiveness, and Research, Operations and Planning, Human Resources, Student Excellence and Success, Workforce Development, students, and community partners to identify, review, and implement AI and emerging technology solutions.
- Lead a cross\-functional team of instructional designers, data analysts, technologists, and program managers supporting AI and emerging technology initiatives.
- Cultivate an environment of ethical innovation, continuous learning, and inclusive institution\-wide participation.
- Maintain awareness of the environmental impact of new and emerging technologies and develop/implement strategies to proactively address these findings.
20% Training \& Development ProgramsStudents* Design and support workshops and micro\-credential pathways in AI literacy, data literacy, responsible AI, and emerging technologies.
- Support experiential learning initiatives (hands\-on labs, hackathons, capstones, internships).
Faculty* Assist with integrating AI into curricula, pedagogy, assessment, and business process workflows.
- Provide training on ethical/responsible AI use, academic integrity, and generative AI tools.
- Support grant writing and AI\-enabled/emerging technology program design initiatives.
Staff \& Administrators* Deliver training on AI\-enhanced productivity tools, automation, decision support, and workflow optimization.
- Support development of certification pathways customized to functional units (e.g., workforce development, academia).
Delivery* Support deployment of multimodal training: LMS\-based modules, webinars, short courses, bootcamps, in\-person sessions, and vendor\-aligned certifications for AI and emerging technology\-related initiatives.
15% AI Strategic Roadmap Execution* Lead execution of the institution’s AI strategic roadmap including planning and launch of related AI or Technology Centers.
- Align AI Center initiatives with institutional AI goals, academic priorities, and technology strategies.
- Prioritize projects based on desirability, impact, feasibility, viability, compliance, and resource needs.
- Develop KPIs, dashboards, and progress\-tracking mechanisms for the AI Strategic Roadmap.
- Provide executive leadership with regular reports on progress, risks, and outcomes.
15% AI Advisory Board Leadership* Establish and facilitate an institution\-wide AI Advisory Board composed of faculty, IT leaders, student representatives, legal/ethics experts, and external community partners.
- Manage the Board’s role in strategic direction\-setting, policy review and development, risk assessment, and oversight of AI governance.
- Coordinate review and approval processes for major AI initiatives, pilots, community partnerships, and vendor engagements.
- Ensure transparent governance and inclusive representation across academic and administrative units.
10% Operational Efficiency \& Automation Initiatives* Partner with administrative units to identify automation opportunities (e.g., admissions triage, scheduling optimization, HR onboarding, document processing).
- Support implementation of AI\-driven predictive analytics (enrollment forecasting, retention modeling, course demand).
- Collaborate with IT to enhance service desk, cybersecurity, and infrastructure monitoring using AI\-enabled tools.
- Promote institution\-wide adoption of AI for workflow optimization and continuous improvement.
10% AI and Emerging Technology Integration Across Campus FunctionsAcademic Innovation* Support review and deployment of intelligent tutoring systems, adaptive learning platforms, generative AI, and other emerging technology solutions for course enhancement.
Program Enablement* Provide administrative staff, faculty and students with AI tools for data analysis, text mining, simulation, and proposal development.
- Promote cross\-disciplinary and community\-based applied solutions using AI and emerging technologies.
Student Services \& Success* Identify and guide implementation of AI\-powered chatbots, virtual advisors, success alerts, well\-being monitoring tools, and related IT solutions.
Campus Operations \& Facilities* Support smart\-campus initiatives such as operations optimization, data analytics, and, improved business workflows using technology.
5% AI Technology Tools \& Governance* Curate, evaluate, and administer institution\-approved AI tools.
- Support the establishment of an ethical and secure usage framework aligned with privacy, cybersecurity, accessibility, and academic integrity standards.
- Oversee creation of sandbox environments and innovation labs that allow experimentation with AI technologies.
- Ensure compliance with federal and state regulations governing data, accessibility, and student protections.
5% AI Conferences, Convenings \& External Partnerships* Represent the institution at regional, national, and global AI conferences, summits, and higher\-ed innovation forums.
- Organize institutional AI and emerging technology convenings, symposiums, advisory summits, and community events.
- Strengthen partnerships with industry, community organizations, government, and technology providers.
- Seek grant funding, philanthropic partnerships, and collaborative technology\-related opportunities.
*Additional Duties:*
- Performs other related duties as assigned.
Minimum Education and Training
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- Master’s degree in Computer Science, Data Science, Information Systems, AI/ML, Education Technology, or related field.
- Demonstrated success leading technology initiatives, digital transformation, analytics, AI innovation, or related functions, typically gained through 8\-10 years of progressively responsible experience.
- Experience with project management, cross\-functional collaboration, and technical evaluation.
- Strong understanding of ethical, legal, and governance considerations for AI use in higher education.
*Preferred Education and Experience:*
- Experience developing AI policies and guidelines, governance models, or enterprise\-level training programs.
- Grant writing experience and familiarity with federal/state funding streams in technology or workforce development.
- Experience planning and launching AI or Technology Centers, labs, or innovation hubs.
*Licenses, Certifications, or Additional Requirements:** ITIL Foundations or PMP for program/process management is a plus.
Minimum Qualifications and Standards Required
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*Knowledge, Skills, and Abilities:*
- Demonstrated knowledge of AI applications and emerging technologies in education, research, and operational environments.
- Strategic Vision \& Execution
- Change Management \& Organizational Leadership
- Ethical \& Responsible AI Practices
- Policy Review and Development
- Communication \& Stakeholder Engagement
- Data\-Informed Decision Making and Data Governance
- Innovation Mindset \& Creativity
- Collaboration \& Consensus Building
- Vendor, Partnership \& Project Management
+ Excellent written and oral communication, analytical, and customer\-service skills.
+ Ability to plan and execute multiple, complex projects concurrently and adapt quickly to changing technology landscapes.
PHYSICAL DEMANDS
The work is medium work which requires exerting up to 50 pounds of force occasionally, and/or up to 30 pounds of force frequently, and/or up to 10 pounds of force constantly to move objects.
WORK ENVIRONMENT
- Standard office environment with data\-center access and limited travel (conferences, training).
- Availability to work outside normal business hours, including on\-call rotations and emergency incident response.
General Employment Information
The College of Southern Maryland is an Equal Opportunity Employer.
Background Checks
The College of Southern Maryland conducts background checks in order to ensure the safety and well\-being of the College's staff and students. The final candidate for this position will be subject to the following background checks: Criminal History Check and Sex Offender Registry Check.
Conflict of Interest policy
No College of Southern Maryland employee shall engage in or have a financial interest, directly or indirectly, in any activity that conflicts or raises a reasonable question of conflict with his or her duties and responsibilities. CSM Employees shall not at any time engage in any outside employment or independent consulting that would adversely affect their employment status or performance as employees at the college, create a conflict of interest, or, with the exception of constitutionally protected activities, would compromise or embarrass the college, or adversely affect professional standing. Any full\-time college employee who also holds a full\-time position or its equivalent in consulting elsewhere (whether permanent or seasonal) will be deemed to have a conflict of interest and will be asked to resign from one of the full\-time positions. Full\-time employees must promptly disclose in writing, on a form available from the Human Resources Office, to the college all other full\-time employment or its equivalent in independent consulting.
Employment Frequently Asked Questions
Click here to find our frequently asked questions: https://www.csmd.edu/employment/frequently\-asked\-questions/index.html
Salary Context
This $84K-$142K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At College of Southern Maryland, 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 $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($113K) sits 48% below the category median. Disclosed range: $84K to $142K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
College of Southern Maryland AI Hiring
College of Southern Maryland has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in La Plata, MD, US. Compensation range: $142K - $142K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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