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About This Role
Engineering a world of possibilities
Reporting to the Chief Information Officer (CIO), the Director of AI (Artificial Intelligence) Acceleration is a key member of the Information Technology (IT) Department and Leadership Team. The Director is a proactive, self‑driven leader responsible for developing and executing a transformative AI vision that moves the university into a new era of operational efficiency, innovation, and productivity. This role anticipates needs, initiates action, and shapes the institution’s future by imagining, designing, and deploying cutting‑edge AI solutions that drive measurable value and lasting business impact. As a strategic leader and champion for change, the Director sparks momentum, fosters cross‑functional collaboration, and sets the standard for responsible and ethical AI adoption.
Leading and managing an agile team with purpose and clarity, the Director of AI Acceleration partners with executive, academic, and administrative leaders, and key stakeholders to proactively identify opportunities and accelerate implementation of agentic‑AI solutions that strengthen institutional capabilities. The role consistently drives forward progress, integrates creative thinking with technical acumen, and delivers meaningful, measurable outcomes that position Mines as a leader in AI‑driven transformation.
This position is currently hybrid, with the expectation that the Director will maintain campus presence a minimum number of days per week in Golden, Colorado.VISIONARY AI STRATEGY & BUSINESS VALUE CREATION
- Envision, develop, and implement an AI strategy collaboratively with the CIO and key stakeholders that aligns with the university’s mission and business, academic, and research priorities.
- Drive transformative change by identifying key opportunities for AI-powered efficiencies, cost optimization, and service excellence across university operations.
- Lead the adoption of AI solutions ensuring scalable, secure, and sustainable value delivery.
- Guide the exploration and integration of emerging AI technologies to enhance business models and advance academic excellence.
- Establish a culture of innovation by fostering experimentation, learning, and continuous improvement in AI-driven initiatives.
AI PRODUCT DEVELOPMENT, INTEGRATION & GOVERNANCE
- Champion the end-to-end lifecycle of AI product development from ideation and prototyping to deployment and iteration.
- Accelerate the adoption of cloud-based and enterprise AI services, ensuring seamless integration and alignment with business strategy.
- Adhere to the Mines AI governance policy ensuring transparency, accountability, and ethical use.
- Ensure data privacy and security best practices are followed in all solutions.
- Define and track outcome‑quality measures and key performance indicators to validate accuracy, minimize hallucinations, and sustain results.
- Empower teams to translate complex AI technologies and concepts into practical solutions that drive stakeholder engagement and operational success.
STAKEHOLDER ENGAGEMENT & ORGANIZATIONAL AI FLUENCY
- Inspire and orchestrate collaboration among academic, administrative, and technical stakeholders to ensure broad alignment and buy-in for the AI vision.
- Chair AI steering committees and advisory groups, proactively seeking input, feedback, and guidance, as well as providing strategic counsel and fostering a community of practice around innovation.
- Lead the development of comprehensive AI literacy programs, training resources, and change management campaigns to elevate skills and confidence across the institution.
- Serve as a trusted advisor and visible ambassador for AI, building strong partnerships and promoting a shared vision of future success.
OPERATIONAL AND TEAM MANAGEMENT
- Lead, mentor, and develop the AI team to ensure high performance, technical excellence, and strong customer service.
- Set and communicate expectations related to service quality and customer experience.
- Recruit and retain top talent; support team growth through training and development.
- Oversee daily operations and ensure that teams prioritize work effectively to meet institutional goals.
- Foster collaboration across IT functions to support operational stability and timely project delivery.
- Forecast staffing and resource needs for ongoing operations and project commitments.
- Implement best practices for operational processes and promote continuous improvement.
Minimum Qualifications:
- Bachelor’s degree from an accredited four-year institution in computer science, data science, engineering, business administration, or a related field; or equivalent advanced training and experience.
- 5+ years of progressive leadership experience in one or more of the following domains: + Executive product management or ownership in technology-driven organizations + Strategic implementation of AI, machine learning, or digital transformation initiatives + Business analysis, process optimization, or IT strategy + Data analytics, governance, or enterprise data strategy + Leading technology enablement or transformational programs
- Visionary leader with deep expertise in AI/ML concepts, generative AI, advanced prompt engineering, and model evaluation.
- Exceptional ability to translate innovative and complex technical ideas into actionable, high-impact strategies for multiple audiences.
- Comprehensive familiarity with cloud and enterprise AI platforms (Microsoft Azure, Google Cloud, AWS).
- Advanced knowledge of data privacy, compliance, and governance frameworks (FERPA, HIPAA, GDPR).
- Outstanding communication, negotiation, and relationship-building skills with executive and technical stakeholders.
- Proven track record of leading organizational transformation and inspiring cross-functional excellence.
Preferred Qualifications
- Master’s degree in computer science, business, data science, engineering, or a related discipline.
- Experience leading AI, data-driven, or transformational initiatives in complex, regulated, or higher education environments.
- Strategic leadership within research, higher education, or public sector organizations.
- Experience designing and leading AI governance initiatives, model transparency, and risk management frameworks.
- Certified Scrum Product Owner (CSPO), Project Management Professional (PMP), Microsoft Certified: Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer, or Certified Analytics Professional (CAP)
- Fluency in advanced AI/ML development, including model evaluation, prompt design, and iterative testing.
- Expertise in AIOps tools and practices for continuous integration, monitoring, and optimization of AI systems.
- In-depth knowledge of Microsoft 365 Copilot, Google Gemini, and other enterprise AI platforms.
- Proficiency in Agile methodologies, strategic product management, and transformational leadership.
Salary and Benefits
$140,000 - $175,000 annual salary
Mines takes into consideration a combination of candidate’s education, training and experience as well as the position’s scope and complexity, the discretion and latitude required in the role, work location, and external market and internal value when determining a salary level for potential new employees.
Colorado School of Mines offers a robust portfolio of benefits for all employees. For this role, that includes:
- Flexible health and dental care options
- Generous sick/vacation time: 13 paid holidays per year – including a week-long winter break for entire campus.
- Fully vested retirement plan on first day of employment, with generous employer contribution
- Tuition benefits (6 credits per year for employees, 50 percent discount for dependents)
- Free RTD Ecopass
All Mines employees also have access to discount programs through the State of Colorado and free tickets for Mines Athletics home games, as well as access to the state of the art Recreation Center (fitness classes and training, swimming pool and more) and equipment rentals through the Outdoor Rec Center. We are proud to have recently opened an on campus daycare center. For more details about benefits at Mines, visit mines.edu/human-resources/benefits.
How to Apply
Complete an online application (personal information, demographic information, veteran status)
- Upload a resume or CV
- Upload a cover letter
Candidates must be currently authorized to work in the United States. Visa sponsorship is not available for this position now nor in the future.
This posting may be used to fill more than one vacancy based on business needs.
References will not be contacted until later in the selection process and you will be informed before that contact is made.
Application review will begin November 2, 2026. This posting will close November 1, 2026 at 11:59 p.m.
It is the intent of Mines to comply with the applicable requirements of the Americans with Disabilities Act and the Americans with Disabilities Act Amendments Act of 2008, and their implementation rules and regulations, in support of equal opportunities for qualified applicants with disabilities. To meet this goal, Mines will make reasonable accommodations during the employment selection process and within our working environment*.*
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on our site as a result of your disability. You can request a reasonable accommodation by contacting our Human Resources team at [email protected] or 303.273.3250 for assistance.
Successful Completion of a Background Investigation is Required for this Position.
About Mines & Golden, CO
When the world looks for answers, the world looks to Mines.
Colorado School of Mines is a top-ranked public university solving the grand challenges facing our society, particularly those related to the Earth, energy and the environment. Founded in 1874 with specialties in mining and metallurgy, Mines’ scope and mission have continually expanded to meet the needs of industry and society. Today, we are the No. 36 public university in the nation, recognized for our innovation and undergraduate teaching in science, technology engineering and math (U.S. News and World Report, 2025).
Mines graduates are change makers, boundary breakers and problem solvers. Since our earliest days, a Mines education has been and continues to be a transformational opportunity, with one of the strongest returns on investment out there for talented STEM students of all backgrounds.
At the same time, Mines faculty members are pushing their fields in new directions, whether that’s manufacturing, space resources, quantum engineering, carbon capture or more. Mines was recently classified as a R1 “Very High Activity” research institution by Carnegie, a notable feat for any university but particularly one of our size.
That size – roughly 8,200 undergraduate and graduate students – also translates to a close-knit campus community, where employees have opportunities to get involved in multiple ways, continued professional learning is valued and everyone can make an impact.
Community Alliance groups bring together employees for professional development, networking, and community involvement, and all Mines employees also have access to the wealth of activities happening every day on campus – nationally-renowned speakers, special events and Mines traditions like Engineering Days, just to name a few.
And don’t get us started on our hometown. We are located in the heart of Golden, Colorado -with its charming historic downtown and nearby hiking trails – and in close proximity to all that Denver and the Rocky Mountains have to offer. That includes the sunny, high-altitude climate and outstanding outdoor recreation opportunities that make the Denver area an ideal place to live, work and play.
Are you looking for an inspiring, mission-driven workplace where you can contribute to solving the world’s problems and educating the next generation of change makers? Are you an individual who values a community where our individual perspectives and experiences enrich the educational and work experience?
Look to Mines.
Additional Information and Reasonable Accommodation Requests
It is the intent of Mines to comply with the applicable requirements of the Americans with Disabilities Act and the Americans with Disabilities Act Amendments Act of 2008, and their implementation rules and regulations, in support of equal opportunities for qualified applicants with disabilities. To meet this goal, Mines will make reasonable accommodations during the employment selection process and within our working environment.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to access job openings or apply for a job on our site as a result of your disability. You can request a reasonable accommodation by contacting our Human Resources team at [email protected] or 303.273.3250 for assistance.
Successful completion of a background investigation may be required for this position.
Equal Opportunity
Colorado School of Mines is committed to equal opportunity for all persons. Mines does not discriminate on the basis of age, sex, gender (including gender identity and gender expression), ancestry, creed, marital status, race, ethnicity, religion, national origin, disability, sexual orientation, genetic information, veteran status or current military service. Further, Mines does not retaliate against community members for filing complaints regarding or implicating any of these protected statuses.
Mines’ commitment to nondiscrimination, equal opportunity and equal access is reflected in the administration of its policies, procedures, programs and activities and in its efforts to achieve a talented student body and workforce.
Through its policies, procedures and resources, Mines complies with federal law, Colorado state law, administrative regulations, executive orders and other legal requirements to prevent discrimination (including harassment or retaliation) within the Mines campus community and to address potential allegations of inequality or concerns for safety.
Colorado's premier engineering and applied science university for 150 years and counting
Salary Context
This $140K-$175K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At COLORADO SCHOOL OF MINES, 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 $212,040 based on 13,780 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,250. This role's midpoint ($157K) sits 26% below the category median. Disclosed range: $140K to $175K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
COLORADO SCHOOL OF MINES AI Hiring
COLORADO SCHOOL OF MINES has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Golden, CO, US. Compensation range: $175K - $175K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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