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PRIMARY PURPOSE
The AI \& Tools Enablement Facilitator is a full\-time OPS position within USF IT that is embedded in the College of Public Health (COPH) to provide dedicated, on\-site support for the practical use of generative AI and Microsoft 365 tools.
This role exists to help faculty and staff integrate tools like Microsoft Copilot into their daily work across departmental functions. The facilitator serves as a hands\-on partner, working directly with individuals and teams to identify opportunities, improve workflows, and build sustainable capability within COPH.
The position maintains a reporting and professional development relationship with USF IT to ensure alignment with university standards, tools, and responsible AI practices. This role is expected to drive measurable improvements in efficiency, user confidence, and adoption of AI\-enabled workflows within the College of Public Health.
ORGANIZATIONAL SUMMARY:
Located in the vibrant and diverse Tampa Bay region of Florida’s gulf coast, the University of South Florida (USF) is a Preeminent State Research University with campuses in Tampa, St. Petersburg and Sarasota\-Manatee. Rated as one of the top places to live in the U.S., Tampa Bay offers a high quality of life, year\-round sunshine, and easy access to top\-rated entertainment. USF is one of the nation’s largest public universities, serving more than 50,000 students with an annual budget of $1\.8 billon. Over the past five years, USF has been the fastest\-rising university in the nation, public or private, on the U.S. News and World Report's list of best universities, which it ranks as the 44th best public university in America.
USF is proud to be an innovating partner within the Tampa Bay region, listed by Forbes as the top emerging tech city in the country.
USF Information Technology (USF IT) provides technology services and support for the University of South Florida. The IT team, led by the Vice President and CIO, provides the following services: Administrative Services, Client Support, Communication Services, Teaching and Learning, Analytics and Reporting, Mobile and Web Services, Consulting Services, Cybersecurity Service and Research Technologies. For more information, please visit: USF Information Technology
ADDITIONAL INFO FOR APPLICANTS:
The selected candidate must have current work authorization in the United States. This position is not eligible for Visa Sponsorship.
IT Core Competencies:
Growth Mindset \- Takes ownership of personal growth and embraces the concept that intelligence and talent can be developed through continuous learning. Willing to take on new challenges, and views failure as an opportunity to grow.
Communication \- Comfortable using a broad range of communication styles, and chooses appropriate, effective ways to communicate. Adapts communication style depending on the audience and situation. Listens and asks questions to develop a better understanding.
Collaboration\- Collaborates with others in the pursuit of common missions, visions, values and goals. Fosters a sense of community within and across teams, building on mutual respect, trust, and drawing on the strengths of others.
Client Obsession\-Client focused when creating solutions or solving problems, believing that everything we do is to earn and keep our clients’ trust.
Ownership\-Takes responsibility, accountability and proactively focuses on areas they can directly influence. Understands their role within the team and recognizes that they share the team’s successes and failures.
Outcome Driven\-Focuses on desired results, business outcomes, and how to achieve them. Takes appropriate actions to ensure commitments are met and results achieved.
PRIMARY JOB DUTIES
AI \& Tools Enablement for Public Health Workflows (45%)
Work directly with COPH faculty and staff to understand discipline\-specific workflows. Identify and implement practical ways to use generative AI and Microsoft 365 tools to improve efficiency, reduce manual effort, and enhance outcomes.
Training \& Applied Facilitation (30%)
Design and deliver targeted, use\-case\-driven training sessions that reflect real work in public health. Facilitate small\-group and one\-on\-one sessions focused on applying tools like Copilot in focused areas. Provide ongoing support to reinforce adoption beyond initial training.
Use Case Development, Documentation \& Impact Tracking (10%)
Capture and document examples of tool usage within COPH, including before/after workflows, time savings, and qualitative improvements. Track engagement and outcomes and provide regular summaries to USF IT to support scaling and program evaluation.
Embedded Liaison \& Program Coordination (10%)
Serve as a consistent, visible point of contact for COPH. Participate in USF IT Client Success team training activities, share insights from COPH, and coordinate with other IT teams as needed to address gaps, escalate issues, or connect users to additional resources.
Content \& Resource Development (5%)
Develop reusable, COPH\-relevant resources such as prompt examples, quick guides, and workflow templates that reflect public health teaching, research, and administrative needs.
MINIMUM EDUCATION \& EXPERIENCE
Bachelor’s degree in Information Systems, Public Health, Communications, Education, or another related field.
Demonstrated experience supporting, training, or enabling others in the use of technology tools.
Experience using Microsoft 365 applications and familiarity with generative AI tools in a professional or academic setting.
Relevant combinations of education and experience may be considered.
Degree Equivalency Clause: Four years of direct experience for a bachelor’s degree.
- Senate Bill 1310\- The Florida Senate (https://www.flsenate.gov/Session/Bill/2023/1310\) is conditional upon meeting all employment eligibility requirements in the U.S.
- SB 1310: Substitution of Work Experience for Postsecondary Education Requirements
- A public employer may include a postsecondary degree as a baseline requirement only as an alternative to the number of years of direct experience required, not to exceed:
- (a) Two years of direct experience for an associate degree;
- (b) Four years of direct experience for a bachelor’s degree;
- (c) Six years of direct experience for a master’s degree;
- (d) Seven years of direct experience for a professional degree; or
- (e) Nine years of direct experience for a doctoral degree
- Related work experience may not substitute for any required licensure, certification, or registration required for the position of employment as established by the public employer and indicated in the advertised description of the position of employment.
- Minimum Qualifications that require a high school diploma are exempt from SB 1310\.
KNOWLEDGE, SKILLS \& ABILITIES
Technical
Strong working knowledge of Microsoft 365 tools.
Familiarity with generative AI tools and their practical applications.
Ability to evaluate and apply tools in real\-world workflows.
Public Health / Academic Context (Preferred)
Understanding of higher education environments.
Familiarity with public health workflows.
Awareness of ethical and responsible AI use.
Communication \& Facilitation
Ability to translate technical capabilities into practical guidance.
Strong relationship\-building skills.
Experience leading training or coaching sessions.
Work Style
Self\-directed and comfortable working independently.
Strong organizational skills.
Curious and proactive mindset.
Ability to balance local COPH needs with USF IT alignment.
Working at USF
With approximately 16,000 employees, the University of South Florida is one of the largest employers in the Tampa Bay area. We are dedicated to cultivating a talented, engaged and driven workforce that strives to be bold. Employees excel in USF‘s rich academic environment, which fosters their development and advancement. In 2025, Forbes recognized USF as one of Florida’s best large employers, ranked No. 1 among the state’s 12 public universities. Our first\-class benefits package includes medical, dental and life insurance plans, retirement plan options, employee and dependent tuition programs, generous leave, and hundreds of employee perks and discounts.
About USF
The University of South Florida is a top\-ranked research university serving approximately 50,000 students from across the globe at campuses in Tampa, St. Petersburg, Sarasota\-Manatee and USF Health. USF is recognized by U.S. News \& World Report as a top 50 public university and the best value in Florida. U.S. News also ranks the USF Health Morsani College of Medicine as the No. 1 medical school in Florida and in the highest tier nationwide. USF is a member of the Association of American Universities (AAU), a group that includes only the top 3% of universities in the U.S. With an all\-time high of $738 million in research funding in 2024 and as a top 20 public university for producing U.S. patents, USF uses innovation to transform lives and shape a better future. The university generates an annual economic impact of more than $6 billion. USF’s Division I athletics teams compete in the American Athletic Conference. Learn more at www.usf.edu .
Compliance and Federal Notices
*This position may be subject to a Level 1 or Level 2 criminal background check.*
Applicants have rights under Federal Employment Laws :
The University of South Florida is an equal opportunity employer that does not discriminate against any employee or applicant for employment based on any characteristic protected by law. The University maintains programs for protected veterans and individuals with disabilities in accordance with all applicable federal and state laws.
Family and Medical Leave Act (FMLA)
Applicants for USF employment are entitled to request reasonable accommodation(s) in the application process. A request is to be made at least five (5\) working days prior to the time the accommodation(s) is needed. Visit the Central Human Resources ADA Accommodations webpage for more information on requesting an accommodation during the application/interview process.
Equal Employment Opportunity
The University of South Florida is an equal opportunity employer that does not discriminate against any employee or applicant for employment based on any characteristic protected by law. The University maintains affirmative action programs for protected veterans and individuals with disabilities in accordance with all applicable federal and state laws. This job description does not constitute an employment contract.
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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At University of South Florida, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
University of South Florida AI Hiring
University of South Florida has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tampa, FL, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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