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Faculty
Description
University of Colorado Anschutz
Department: School of Medicine, Office of the Dean
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Job Title: Senior Associate Dean for AI and Health Data Science
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Position \#00849544 – Requisition \#40183
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Job Summary:
The Senior Associate Dean for AI and Health Data Science provides strategic leadership for artificial intelligence, data governance, and health data science across the University of Colorado School of Medicine. Reporting to the Dean, this role leads the development and execution of the School’s AI and data strategy; advances AI\-enabled innovation across research, clinical care, education, and operations; and aligns institutional efforts with health system and university partners. The Senior Associate Dean oversees a portfolio of data, informatics, and information units; builds shared services and capabilities that support faculty, learners, and leaders; and promotes the responsible, equitable, and effective use of AI. This role will shape how AI and health data science strengthen academic medicine, improve care and learning, and expand the School’s institutional impact.
Key Responsibilities
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*Strategy and Vision*
- Develop and execute the School’s long\-term enterprise AI roadmap across research, clinical care, education, and business operations.
- In partnership with the respective School leaders, integrate data science, machine learning, and generative AI literacy into undergraduate and graduate medical education, ensuring physicians understand both the promise and limitations of AI.
- Guide the School’s transition from dashboard\-based reporting to AI\-enabled and agentic decision support for departmental and school leadership.
- Drive AI\-enabled transformation of administrative, academic, and operational workflows across all mission areas.
- Establish data and AI readiness standards for data quality, interoperability, and documentation to support trustworthy institutional use.
- Define and report metrics that demonstrate the value and impact of the School’s AI and data investments.
- Partner with advancement leadership to shape AI\- and data\-focused philanthropic priorities, donor engagement strategies, and major\-gift proposals.
*Portfolio Leadership and Operations*
- Under the direction of the Vice Chancellor of Health Affairs, provide oversight of Health Data Compass, the Colorado Center for Personalized Medicine, and School of Medicine Information Services, ensuring operational excellence, sustainability, and service quality.
- Align data engineering, AI/ML, informatics, and analytics capabilities as an integrated portfolio of shared services for the School and its departments.
- Oversee the development, technical validation, and pilot deployment of machine learning and deep learning tools within Electronic Health Record environments and clinical workflows, including predictive clinical decision support.
- Working with key leaders in various School units, enable AI\-ready access to School business data, including finance, human resources, grants, space, and operations, to support faster and better\-informed decisions.
- Steward the biobank, enterprise data warehouse, and related data assets as a coordinated portfolio that advances research, innovation, and commercial partnerships.
- Recruit, develop, and retain high\-performing teams and technical talent across the School’s AI and data portfolio.
- Support departments in recruiting AI\- and data\-intensive faculty by bringing technical expertise to candidate evaluation and strategic hiring decisions.
- Establish governance structures, compliance frameworks, and operational guardrails that support secure, ethical, balanced, and responsible AI use, with attention to data privacy, bias mitigation, and evolving regulatory requirements.
*Partnerships, Enablement, and Stakeholder Engagement*
- Partner with the Dean/Vice Chancellor for Health Affairs, Executive Vice Deans and School leaders to advance the application of AI in clinical care, quality, and health system performance.
- Partner with education leadership to build AI and data literacy and strengthen capability among faculty, staff, trainees, and students.
- Lead workshops, training programs, and communities of practice that build faculty capability in the use of generative AI for teaching, assessment, and administrative efficiency.
- Under the designated Executive Vice Deans, serve as a key liaison between the School of Medicine, UCHealth, Children’s Hospital Colorado, university computing and data science partners, and external technology leaders to align priorities, strengthen alliances, and advance shared AI goals.
- Engage department chairs, center directors, and institute leaders to align priorities, accelerate shared initiatives, and expand institutional impact.
- Develop strategic partnerships and resource opportunities that advance the School’s AI agenda, including federal grants, philanthropy, and industry collaborations.
Key Relationships
Reports to
- John Sampson, MD, PhD, MBA \- Dean, School of Medicine and Vice Chancellor of Health Affairs and President, University of Colorado Medicine
Direct Reports
- Director of School of Medicine Information Services
Other Key Relationships
- Executive Vice Dean – Clinical / Research/ Quality
- Executive Vice Dean – Education
- Executive Vice Dean – Finance and Administration
- Senior Associate Dean – Clinical Affairs
- Senior Associate Dean – Biomedical Research
- Senior Associate Dean – Basic Science
- Associate Dean – Centers and Institute
- Vice Chancellor \& CIO, Information Strategy and Services
- Vice Chancellor for Innovation and Biotechnology
- Director, Health Data Compass
- Director, Colorado Center for Personalized Medicine
- UCHealth Senior Leadership
- Children’s Hospital Colorado Senior Leadership
- VA Eastern Colorado Health System Senior Leadership
- Denver Health Senior Leadership
- National Jewish Health Senior Leadership
- CU Anschutz Medical Campus Senior Leadership
- CU Medicine Board of Directors
- University of Colorado Board of Regents
- Department Chairs and Department Administrators
- Community leaders
Work Location:
Onsite – this role is expected to work onsite and is located in Aurora, Colorado.
Why Join Us:
The CU Anschutz School of Medicine offers comprehensive, lifelong, interdisciplinary learning for health care professionals. With state\-of\-the art laboratories for discovery and innovation, a commitment to decreasing health disparities and increasing health equity, and faculty who provide world\-class clinical care, the CU Anschutz School of Medicine is transforming the health care landscape.
Why work for the University?
We have AMAZING benefits and offerexceptional amounts of holiday, vacation and sick leave! The University of Colorado offers an excellent benefits package including:
- Medical: Multiple plan options
- Dental: Multiple plan options
- Additional Insurance: Disability, Life, Vision
- Retirement 401(a) Plan: Employer contributes 10% of your gross pay
- Paid Time Off: Accruals over the year (based on percentage of time)
- Vacation Days: 22/year (maximum accrual 352 hours)
- Sick Days: 15/year (unlimited maximum accrual)
- Holiday Days: 11/year
- Tuition Benefit: Employees have access to this benefit on all CU campuses
- ECO Pass: Reduced rate RTD Bus and light rail service
There are many additional perks \& programs with the CU Advantage. Qualifications:
Minimum Qualifications:
*Applicants must meet minimum qualifications at the time of hire.*
- Doctoral degree (PhD, MD, MD/PhD, or equivalent) in a relevant field from an accredited institution.
- Minimum of 7 years of progressive leadership experience in academic medicine, biomedical informatics, health data science, or health system technology.
- Demonstrated expertise in AI/ML, biomedical informatics, healthcare data infrastructure, or related fields.
- Eligibility for appointment as a faculty member at the rank of Professor.
Preferred Qualifications:
- Demonstrated success leading a research, informatics, AI, or data science organization at the scale of a department, center, or comparable enterprise within an academic medical center.
- Substantive track record in the application of AI/ML to biomedicine, healthcare, or health system operations.
- Experience setting strategy, managing resources, and operating across multiple units with distinct missions.
- Demonstrated success leading interdisciplinary initiatives in large, matrixed organizations.
- Familiarity with the privacy, security, ethical, and regulatory landscape governing health data and AI.
Knowledge, Skills and Abilities:
- Strategic vision for the application of AI and data science in academic medicine and health systems.
- Ability to translate between technical teams and institutional leadership and to build consensus across diverse stakeholders.
- Exceptional written, verbal, and interpersonal communication skills.
- Ability to build and sustain effective working relationships across all levels of the institution.
- Strong financial and operational management skills, including familiarity with academic medical center budgeting.
- Demonstrated ability to plan, prioritize, and execute complex initiatives while meeting deadlines.
How to Apply:
For full consideration, please submit the following document(s):
1\. A letter of interest describing relevant job experiences as they relate to listed job qualifications and interest in the position
2\. Curriculum vitae / Resume
3\. Five professional references including name, address, phone number (mobile number if appropriate), and email address
Applications are accepted electronically ONLY at www.cu.edu/cu\-careers.
Questions should be directed to: Mark Couch, [email protected]
Screening of Applications Begins:
Applications will be accepted until finalists are identified, but preference will be given to complete applications received by June 16, 2026\. Those who do not apply by this date may or may not be considered.
Anticipated Pay Range:
The starting salary range (*or hiring range*) for this position has been established as HIRING RANGE: $750,000 to $1,000,000
The effort/FTE of the role will be 0\.5 FTE
The above salary range (*or hiring range*) represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting. This position is not eligible for overtime compensation unless it is non\-exempt.
Your total compensation goes beyond the number on your paycheck. The University of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line.
Total Compensation Calculator:
Equal Employment Opportunity Statement:
The University of Colorado (CU) is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities.
ADA Statement:
The University will provide reasonable accommodations to applicants with disabilities throughout the employment application process. To request an accommodation pursuant to the Americans with Disabilities Act, please contact the Human Resources ADA Coordinator at [email protected].
Background Check Statement:
The University of Colorado Anschutz Medical Campus is dedicated to ensuring a safe and secure environment for our faculty, staff, students and visitors. To assist in achieving that goal, we conduct background investigations for all prospective employees.
Vaccination Statement:
CU Anschutz strongly encourages vaccination against the COVID\-19 virus and other vaccine preventable diseases. If you work, visit, or volunteer in healthcare facilities or clinics operated by our affiliated hospital or clinical partners or by CU Anschutz, you will be required to comply with the vaccination and medical surveillance policies of the facilities or clinics where you work, visit, or volunteer, respectively. In addition, if you work in certain research areas or perform certain safety sensitive job duties, you must enroll in the occupational health medical surveillance program.
Application Materials Required: Cover Letter, Resume/CV, List of References
Job Category: Faculty
Primary Location: Aurora
Department: U0001 \- Anschutz Med Campus or Denver \- 20029 \- SOM\-DEAN DO ADMINISTRATION
Schedule: Part\-time
Posting Date: Jun 9, 2026
Unposting Date: Ongoing
Posting Contact Name: Mark Couch
Posting Contact Email: [email protected]
Position Number: 00849544
Salary Context
This $750K-$1000K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $180K across 2130 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 4,133 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At University of Colorado, 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 $185,000 based on 13,200 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($875K) sits 373% above the category median. Disclosed range: $750K to $1000K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
University of Colorado AI Hiring
University of Colorado has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Aurora, CO, US. Compensation range: $1000K - $1000K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 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 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). 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 (1,901) and senior (1,663) 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 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 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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