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About This Role
University Operations:
The University Operations division at UCF is committed to creating a supportive and welcoming environment for our faculty, staff, students, and the broader community. We take pride in delivering exceptional service, sharing our expertise, and upholding the highest standards to ensure a world-class campus experience.
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The Opportunity:
UCF IT is looking to hire an AI Platform Engineer II. This position supports UCF’s AI platform operations by helping operate, monitor, and maintain core AI services, including AI Gateway, API Management, model-serving environments, and local GPU compute resources. This position supports reliable AI service delivery, local model life cycle management, and operational readiness for model hosting, fine-tuning, training, and inference workloads in alignment with university governance, privacy, and security standards.
Classification Title: Systems Engineer II
Responsibilities:
- Operate, monitor, and support AI platform services including the AI Gateway, API Management, model-serving endpoints, and related back-end services. Monitor availability, latency, errors, capacity, and service health; troubleshoot routine issues and escalate complex incidents to senior staff.
- Assist with operating local GPU nodes and compute environments used for model hosting, fine-tuning, training, and inference workloads. Support resource utilization, environment configuration, operational readiness, and routine maintenance of compute services.
- Maintain the life cycle of approved local models, including version tracking, deployment support, retirement planning, documentation, and alignment with governance, security, and operational standards.
- Support CI/CD pipelines, infrastructure-as-code configurations, container deployments, observability tooling, and repeatable deployment patterns for AI services and integrations.
- Apply established governance, privacy, and security standards to AI deployments, including authentication, authorization, logging, data handling, and responsible AI controls. Support Entra ID, OAuth/OIDC, and role-based access patterns for AI platform services.
- Maintain architecture diagrams, standard operating procedures, runbooks, model inventories, service dashboards, usage reports, cost reporting, and capacity metrics for AI platform operations.
- Assist senior engineers, AI Center of Excellence staff, and campus partners with routine platform questions, on boarding support, workshops, and operational guidance related to supported AI services. Other duties as assigned.
Minimum Qualifications:
Bachelor’s degree and 2 years of relevant experience; or High School Diploma (or equivalent) and 6 years of relevant work experience in lieu of degree; or an equivalent combination of education and experience pursuant to Fla. Stat. 112.219(6) .
Preferred Qualifications :
- Experience supporting enterprise AI, machine learning, cloud, or platform services, including API management, model-serving environments, and application integrations.
- Knowledge of containerization and modern deployment technologies such as Docker, Kubernetes, infrastructure-as-code, CI/CD pipelines, and automated deployment practices.
- Experience administering or supporting Linux-based server environments, GPU-enabled compute infrastructure, high-performance computing resources, or cloud-hosted AI workloads.
- Familiarity with identity and access management technologies, including Microsoft Entra ID, OAuth 2.0, OpenID Connect (OIDC), role-based access controls, and enterprise authentication frameworks.
- Experience utilizing monitoring, observability, and reporting tools to track service health, system performance, capacity utilization, availability, and operational metrics.
- Knowledge of AI governance, data privacy, cybersecurity, and responsible AI principles, including model lifecycle management, auditability, documentation, and compliance with organizational standards.
Special Instructions to the Applicants:
Position requires a valid Class E driver’s license. The position may involve driving to various locations on and off campus to conduct University business.
The anticipated salary range for this position is $64,518 to $72,000. The final salary will be determined based on the candidate's qualifications, experience, and internal equity considerations.
If you are selected as the final candidate for an employment opportunity, both your position and salary will be significantly based upon the information that you have provided in your application for employment. We urge you to please take the time to complete the application in its entirety.
All applicants must be authorized to work for any U.S. employer. Visa sponsorship is not available for this position, and the university cannot accommodate H‑1B transfers or employment-based visa processing for individuals currently sponsored by another employer.
This role requires the successful candidate to work on-site at UCF as their primary work location. On-site presence is an essential function of this role.
Classification Title: Systems Engineer II
Are you ready to unleash YOUR potential?
As a next-generation public research university and Forbes-ranked top employer in Florida, we are a community of thinkers, doers, creators, innovators, healers, and leaders striving to create broader prosperity and help shape a better future. No matter what your role is, when you join Knight Nation, you’ll play an integral role at one of the most impactful universities in the country. You’ll be met with opportunities to connect and collaborate with talented faculty, staff, and students across 12 colleges and multiple campuses, engaging in impactful work that makes a positive difference. Your time at UCF will provide you with many meaningful opportunities to grow, you’ll work alongside talented colleagues on complex projects that will challenge you and help you gain new skills, and you’ll have countless rewarding experiences that go well beyond a paycheck.
Working at UCF has its perks! UCF offers:
- Benefit packages, including Medical, Dental, Vision, Life Insurance, Flexible Spending, and Employee Assistance Program
- Paid time off, including annual and sick time off and paid holidays
- Retirement savings options
- Employee discounts, including tickets to many Orlando attractions
- Education assistance
And more…For more benefits information, view the UCF Employee Benefits Guide . *
Dive into our Total Rewards Calculator to discover the diverse selection available to you, giving you a glimpse into the benefits that together shape your comprehensive rewards package at UCF.
Unless explicitly stated on the job posting, it is UCF’s expectation that an employee of UCF will reside in Florida as of the date the employment begins.
Department
UCF IT Work Schedule
Monday - Friday, 8:00 AM - 5:00 PM Type of Appointment
Regular Expected Salary
$64,518.00 to Negotiable Job Posting End Date
10-16-2026-12-00-AM
The University of Central 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.
As a Florida public university, the University of Central Florida makes all application materials and selection procedures available to the public upon request.
UCF is proud to be a smoke-free campus and an E-Verify employer.
For general application or posting questions, please email [email protected] .
If an accommodation due to a disability is needed to apply for this position, please email [email protected] .
Salary Context
This $64K-$72K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At University of Central 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 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($68K) sits 68% below the category median. Disclosed range: $64K to $72K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
University of Central Florida AI Hiring
University of Central Florida has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Orlando, FL, US. Compensation range: $72K - $85K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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