Interested in this AI/ML Engineer role at American Nurses Association ANA?
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Career Title: Vice President of Artificial Intelligence (A.I.), and Digital Health Programs
Department: Nursing Programs Salary: Competitive salary commensurate with experienceFLSA: ExemptNote: This position is grant\-funded for an expected three\-year term and is contingent upon continued grant funding. Career Summary:
The American Nurses Enterprise (ANE) is seeking a Vice President (VP) of Artificial Intelligence (A.I.) and Digital Health Programs to lead and support a highly skilled, high\-performing team of up to three direct reports.
As the VP of AI and Digital Health Programs, you will be a nationally recognized leader with deep expertise in artificial intelligence, emerging technologies, and clinical safety to lead ANE’s strategy for AI across nursing and healthcare. This role will guide ANE’s work at the intersection of technology, governance, and professional practice, ensuring that AI solutions enhance care quality, protect patient safety, strengthen nursing workflows, and uphold ethical standards.
Moreover, you will serve as the leader representing the ANE as a trusted authority for nurses, health systems, policymakers, industry partners, and the public, translating complex technology into safe, practical, and evidence\-based recommendations for the profession.
Join the American Nurses Enterprise (ANE) and be part of the team building a healthy world through The Power of Nurses™. Our goals are to (1\), Elevate the Profession of Nursing Globally and (2\), Evolve the Practice of Nursing to Improve Health, Health Care, and Health Equity and (3\), Ensure the Professional Success of Nurses. Our core values: Trusted, Inclusive, Innovative and Empowered guide everything we do. We are committed to creating a supportive and dynamic workplace where employees can thrive.
We understand the importance of work\-life balance and offer flexible work arrangements and generous paid time off. Our modern office spaces are designed to foster collaboration and creativity. The collaborative culture and supportive team environment make ANE a great place to grow your career. What You Will Do:
- Partner with the executive leadership team to align programs and initiatives with the ANE’s mission, values, and strategic priorities.
- Direct departmental budget development and reconciliation, ensuring accountability for grant funding, contract compliance, and resource stewardship.
- Develop and implement mechanisms to evaluate and report on the impact of ANE’s programs, products, and services.
- Provide executive\-level reports and data visualizations that demonstrate organizational influence on nursing, healthcare delivery, and health policy.
- Identify and advance opportunities for collaboration, business development, and policy engagement.
- Provide strategic support for the design, development, and distribution of products and services across the Enterprise, ensuring relevance and measuring impact across the product lifecycle.
- Represent the Enterprise at conferences, summits, and forums to promote visibility and thought leadership.
- Lead special projects and strategic initiatives as assigned to address emerging priorities and opportunities.
Program \& Resource Development
- Direct the creation of content and resources, that may include, educational resources, toolkits, competencies, and training programs to support AI literacy and safe adoption among nurses.
- Provide subject matter expertise for webinars, position statements, continuing education programs, and national convenings.
- Lead or support research related to AI effectiveness, safety, bias mitigation, and impact on nursing practice and workforce well‑being.
Stakeholder Engagement \& Representation
- Serve as ANE’s national representative to governmental agencies, professional societies, technology coalitions, and cross‑industry consortia related to AI in healthcare.
- Build collaborations with health systems, vendors, academic institutions, and policy groups to promote nurse\-led AI governance.
What you bring to the American Nurses Enterprise: Required Education
- Master’s degree in Nursing, Informatics, Healthcare Leadership, Data Science, or related field.
- 3\+ years of experience in nursing informatics, clinical technology integration, digital transformation, or AI‑related roles.
- Minimum of 3\-5 years of executive\-level experience.
- Minimum of 10 years of progressive leadership experience in nursing, healthcare non\-profits and/or associations, health systems, policy, or global affairs.
- National certification in informatics or executive leadership ore related field (e.g., NI\-BC\- Nursing Informatics\-Board Certified).
- Record of publications or presentations on AI, nursing informatics, or tech\-enabled care innovation.
Preferred Qualifications
- Preferred (not required)\- Doctoral degree (DNP, PhD, Dr. of Public Health, or equivalent)
- Registered Nurse (RN) with an active, unrestricted license.
- Experience leading national initiatives, policy development, or multi‑stakeholder collaborations.
- Experience evaluating or implementing AI tools.
Skills
- Strong written and verbal communication, including public speaking, with ability to translate complex technical concepts into clear guidance for broad audiences.
- Relationship\-building with healthcare leaders, boards, government, and global partners.
- Expertise in organizational design, project management, data analytics, and performance reporting.
- Critical thinking, problem\-solving, and sound decision\-making.
- Proven ability to manage competing priorities in complex environments.
- Business acumen with focus on operational effectiveness. Proficient in Microsoft Office Suite.
- Deep understanding of AI applications in healthcare—including risks, regulatory landscape, ethical considerations, and safety implications.
- Demonstrated expertise in workflow redesign, clinical decision support systems, or data enabled care models.
Core Competencies
- Nursing Informatics and AI literacy
- Ethical and safe technology governance
- Evidence\-based practice and quality improvement
- Strategic communication and thought leadership
- Policy interpretation and regulatory awareness
- Cross\-sector collaboration and partnership building
- Systems thinking and workforce transformation
What ANE Offers You:* Join us and support more than 5 million Registered Nurses in the United States.
- Every role within ANE contributes to a healthier world through The Power of Nurses™.
- An opportunity to help transform a 129\-year\-old organization to meet the future needs and demands within Health Care.
- Be a role model for embracing and empowering the uniqueness of every employee.
- Continuously innovating through creative and strategic initiatives.
- Exceptional benefits including but not limited to 401K retirement contributions of up to 7%, generous PTO which includes the week\-off between Dec 25 and Jan 1, in addition to Personal Days\-off, 11 paid Holidays, excellent health/medical benefits, and much more.
- Commitment to your career development and advancement through ANE learning and development programs (internally and externally).
Work Schedule:
Hybrid employees must work a minimum of 20% in the office. Location:
ANE Headquarters office located at: 8403 Colesville Road, Suite 500, Silver Spring, MD 20906 Learn more about the American Nurses Enterprise:
https://www.nursingworld.org/ana\-enterprise\-jobs/
https://www.linkedin.com/company/american\-nurses\-association The American Nurses Enterprise:
Founded in 1896, the American Nurses Enterprise is the family of nonprofit organizations that comprise of the American Nurses Association (ANA), the American Nurses Credentialing Center (ANCC), and the American Nurses Foundation (ANF). Equal Opportunity Employer:
The ANE is an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.
Salary Context
This $190K-$213K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At American Nurses Association ANA, 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 $218,750 based on 3,817 positions with disclosed compensation. This role's midpoint ($201K) sits 8% below the category median. Disclosed range: $190K to $213K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
American Nurses Association ANA AI Hiring
American Nurses Association ANA has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Silver Spring, MD, US. Compensation range: $135K - $213K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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