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Apply Now →About This Role
The Lead Faculty is a member of the faculty (with rank appropriate to the educational and professional background of the individual) who also holds an administrative appointment related to managing the faculty within a specific academic program or set of academic programs. With accountability for coaching and managing faculty, the Lead Faculty exemplifies teaching and student support strategies, while upholding faculty performance standards and student engagement policies (including those related to faculty presence, participation, feedback, and outreach). With responsibilities for teaching and instruction, the Lead Faculty provides a meaningful student learning of the course and programmatic learning outcomes in the curriculum and proactively supports all facets of the learning environment. The Lead Faculty provides and champions education through Colorado Technical University's Professional Learning Model that assists program graduates to fulfill the evolving needs of the marketplace.
The Lead Faculty has a normal course load each academic year to teach 2 courses (8 to 12 quarter hours) each quarter, with a total of 8 courses (32 to 48 quarter hours) per academic year. This allows the Lead Faculty to focus on faculty coaching, managing, and administrative responsibilities. The Lead Faculty successfully completes a minimum of 8 hours of training and professional development, following an appropriate plan during the academic year.
Principal Duties and Responsibilities Lead Faculty Performs as a Faculty Member
- Performs responsibilities (as a faculty member) as outlined in this job description and in accordance with the provisions of the Faculty Handbook (including faculty expectations) and the Colorado Technical University Employee Handbook.
- Participates in periodic and annual faculty evaluation requirements (including class observations) to provide a strong, student\-focused educational environment through consistent adherence to student competencies, assessments, and pedagogy, in compliance with Colorado Technical University policies.
Principal Duties and Responsibilities Lead Faculty Performs as a Member of Faculty Management
- Performs responsibilities (as both a faculty member and as a Lead Faculty) as outlined in this job description and in accordance with the provisions of the Faculty Handbook and the Colorado Technical University Employee Handbook.
- Contributes to the new faculty onboarding and training process, including needs assessment, interviews of potential candidates (as applicable), and coaching, and mentoring.
- Coaches, manages, and inspires faculty through the instructional process, driving compliance with Colorado Technical University's academic policies and procedures and striving to continuously improve the level of instructional expertise.
- Observes faculty, monitors applicable reports and dashboards, and reviews course elements to ensure quality of instruction and faculty activities meet Colorado Technical University's faculty expectations and policy requirements.
- Reviews and provides feedback on faculty performance, including periodic performance reviews.
- Reviews student\-based and other evaluation sources, shares evaluations with faculty, identifies opportunities for improvement, and works collaboratively to implement solutions.
- Reviews faculty loading and scheduling to ensure appropriate student/faculty ratios and facility utilization.
- Collaborates with academic personnel to develop a faculty pool with appropriate academic and professional qualifications.
- Provides support to faculty in times of need by professionally and expediently answering questions, addressing faculty issues, and resolving faculty complaints and appeals.
- Participates in the initial collection and periodic updates of all documentation required to meet accreditation and regulatory requirements for the faculty file.
- Provides support to students in times of need by professionally and expediently answering questions, addressing student issues, and resolving student complaints and appeals.
- Monitors faculty follow\-up with students concerning missing work and/or poor academic progress, working with the Program Director/Dean or Vice President for Academic Operations on Colorado Technical University's student retention and success initiatives.
- Participates in surfacing needs, specifying outcomes, identifying alternatives, and implementing technology and support innovations.
- Participates in surfacing needs, specifying outcomes, identifying content, and reviewing completed faculty training and professional development modules (including in\-service activities) related to annual plan completion.
- Attends required University and departmental meetings, including graduation ceremonies, Doctoral Symposia (as applicable), and other formal functions as appropriate (subject to resource availability).
- Participates in standing committees of the University and department (e.g., Program Committee, IRB, etc.) based on University and departmental needs.
- Participates in the design and/or development of new or significantly revised programs and/or courses based on departmental need and in consultation with the pertinent University Dean and Program Chair.
- Works with University and department administration to implement academic policies, procedures, educational policies, and assessment plans that are compliant with HLC and programmatic accreditation standards and state agency regulations.
- Communicates consistently and effectively with the department administration, campus administration (if applicable), students, faculty colleagues, and other Colorado Technical University staff and administration.
- For campus\-based Lead Faculty, maintains membership in relevant professional and community organizations, with attendance and participation at meetings, seminars, and events as appropriate to enhance the reputation of the University and enable pertinent student participation in community service projects.
- Provides flexibility in scheduling, including evenings and weekends to meet student and business requirements.
- Performs other duties as assigned.
Knowledge, Skills, and Abilities; Competencies
- Willingness and demonstrated ability to support and foster student and faculty achievement at all levels, rather than simply evaluate the completion of requirements and/or responsibilities.
- Interpersonal and relationship building skills.
- Project and program management skills with a focus on successful completion.
- Focus on data and outcome metrics to gauge success and highlight areas for improvement.
- Drive for and pursuit of innovation.
- Strong leadership and strategic planning skills.
- Strong analytical and change management skills.
- Experience with computerized learning management systems and education technology tools strongly preferred.
- Proficiency with standard office applications on personal computers.
- Ability to read, comprehend, interpret, and implement accreditation criteria, state agency regulations, and academic policies and procedures.
- Ability to effectively present information to students, faculty colleagues, and academic and campus leaders.
- Ability to manage multiple tasks and successfully meet deadlines.
- Ability to work effectively, cooperatively, and flexibly in a team environment.
- Ability to physically work in the United States while performing all responsibilities of the position for Colorado Technical University.
Qualification Preferences
- Terminal degree in Business/Management from a regionally accredited institution in higher education accredited by an agency recognized by the U.S. Department of Education (or international equivalent) required.
- 18 graduate hours in Business Analytics or Technology Management
- 3 to 5 years of experience working with adult learners in support areas.
- 5 years teaching experience at the collegiate level, with diverse online, blended, and campus\-based experiences a plus.
- 5 years of professional experience in an organizational setting relevant to Colorado Technical University's programs preferred, with a diverse set of industry, academic, strategic, and personnel experiences a plus.
- 1 to 3 years of progressive experience managing or coordinating faculty teams preferred, including hiring, support, evaluation, and development responsibilities, with online, blended, and/or campus\-based faculty management experience a plus.
- Experience working with a variety of functional areas preferred.
What we offer\*
- Pay: $82,400 \- $95,000 per year
- *Most benefits apply to full\-time employees. Some benefits apply to part\-time employees as well. Benefits may vary by location and position and are subject to change at any time. Ask your recruiter for full details and information about eligible dependents.*
About Colorado Technical University (CTU)
For 55 years, Colorado Technical University has helped students fit a real\-world education into their busy daily lives. With nearly 80 degree programs and concentrations in which students can pursue a variety of degrees at the Associate, Bachelor's, Master's and Doctoral level. CTU provides flexible online classes, accessible through the Virtual Campus and the innovative, award winning CTU Mobile app. CTU has two brick and mortar campus locations in Colorado Springs and Denver South, Colorado. With the help of faculty and industry professionals, CTU has awarded over 109,000 degrees to traditional campus and online students since 1965\. For more information about CTU, visit www.coloradotech.edu.
*Equal Opportunity Employer*
*Colorado Technical University is committed to a policy of equal employment opportunity and considers all persons without regard to age, color, disability, genetic information, marital status, national origin, race, religion, sex, sexual orientation, veteran status or any other status protected by applicable federal, state or local law.*
Req Benefits: Paid time off \* Paid sick leave \* Paid holidays \* Comprehensive medical, pharmaceutical, dental, and vision benefits \* Health savings and flexible spending accounts \* 401(k) savings plan with company match \* Employee Stock Purchase Plan (ESPP) \* Company paid life insurance and disability insurance \- subject to eligibility \* Company paid tuition assistance \- subject to eligibility and approval \* Employee Assistance Program (EAP) \* Prenatal and adoption assistance \* Additional ancillary programs are available upon benefit enrollment eligibility \*Most benefits apply to full\-time employees. Some benefits apply to part\-time employees as well. Benefits may vary by location and position and are subject to change at any time. Ask your recruiter for full details and information about eligible dependents.
Compensation: $82,400 to $95,000
Salary Context
This $82K-$95K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Perdoceo Education Corporation, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($88K) sits 59% below the category median. Disclosed range: $82K to $95K.
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.
Perdoceo Education Corporation AI Hiring
Perdoceo Education Corporation has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $95K - $1254K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
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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