Interested in this AI/ML Engineer role at Hofstra University?
Apply Now →Skills & Technologies
About This Role
Position Details
--------------------
Position Information
About Hofstra
Hofstra University, a nationally ranked and recognized private university in Hempstead, New York, invites nominations and applications for the role of Senior Vice President for Financial Affairs and Treasurer.
Hofstra University enrolls over 6,000 undergraduate students and nearly 4,000 graduate students in 13 schools, which feature a variety of departments, as well as a number of institutes and centers. Hofstra offers 175 undergraduate programs and approximately 200 graduate programs in Liberal Arts and Sciences, Business, Communication, Education, Health Professions and Human Services, Engineering and Applied Science, and Honors studies, as well as a School of Law and a School of Medicine. The student\-faculty ratio is 13 to 1, and the average undergraduate class size is 21\. Athletics contribute to the vibrance of the Hofstra community, with 21 varsity sports teams that compete at the NCAA Division I level in the Colonial Athletic Association.
The new Senior Vice President will join a dynamic leadership team that has been steering the institution into an exciting new era, following the appointment of its ninth and first female president,Dr. Susan Poser, in August 2021, and provost, Dr. Charlie Riordan, in July 2022\. The leadership team is investing heavily in academic programs for students while also growing the scholarly and research enterprise and reputation of the University. In 2025, Hofstra University earned the distinction of a High Spending and Doctorate Production University (R2\) by the Carnegie Classification of Institutions of Higher Education, marking a significant milestone in the University’s academic and research trajectory. In addition, Hofstra recently launched an ambitious ten\-year strategic plan, Hofstra 100, which reaches out to the University’s centennial in 2035\. This plan focuses on academic excellence and bridges Hofstra’s century of growth and accomplishment to the student\-centric, technology\-forward needs of the next era. In collaboration with the president, University leadership, and the Board of Trustees, the new senior vice president will serve both as a lead fiscal steward of the University and as a key strategic advisor for the president, supporting a community dedicated to faculty excellence, student success, and organizational agility as it strives to achieve its strategic aspirations.
Position Title Senior Vice President for Financial Affairs and Treasurer
Position Number 899023
Position Category Administration
School/Division Office of the President (division)
Department Financial Affairs
Full\-Time or Part\-Time Full\-Time
Description
Reporting to the president, the Senior Vice President (SVP) for Financial Affairs and Treasurer will play a critical leadership role in advancing Hofstra’s strategic goals. The SVP serves as a member of the president’s cabinet and a member of the senior leadership team, responsible for leading and overseeing the institution’s financial strategy, facilities and operations, and stewardship. This position provides strategic leadership to ensure the institution’s financial health, sustainability, and operational efficiency, while supporting its mission, strategic priorities, and academic objectives. With direct oversight and responsibility for the facilities and operations division, the SVP will be positioned to cultivate and advance new partnerships and synergies among financial planning, facilities, and operations.
The successful candidate for this position will demonstrate a commitment to Hofstra’s mission and will be energized by the future opportunities for Hofstra University. The community desires a leader who has demonstrated experience and acumen in fiscal responsibility and brings a reputation for advancing and implementing creative, innovative, and entrepreneurial strategies and solutions. The leader will bring a deep understanding of financial modeling and analysis, budgeting, and capital and financial transactions; an understanding of current and future trends in higher education; a demonstrated ability to implement strategies to support the long\-term financial success of an institution; and a commitment to clear and thoughtful communication with constituents.
Qualifications
The new executive will have at least 15 years of experience in increasingly responsible positions in financial systems and operations, including successful fiscal, administrative leadership, and managerial experience in senior level positions, preferably in higher education or a comparable sector. An earned master’s degree in business administration, finance, accounting, or related field is required as is a demonstrated understanding of GAAP.
Preferred Qualifications
Special Instructions
All applications, nominations, and inquiries are invited. Applications should include, as separate documents, a CV or resume and a letter of interest addressing the themes in the leadership profile.
WittKieffer is assisting Hofstra University in this search. Applications will be received until the position is filled, however, we strongly encourage candidates to submit their materials as soon as possible for full consideration. Application materials should be submitted using WittKieffer’s candidate portal.Nominations and inquiries can be directed to: Jessica Herrington, Sarah Palmer, and Kim Migoya at HofstraSVP@wittkieffer.com
Deadline Open until filled
Date Posted 03/24/2026
EEO Statement
Hofstra University is an equal opportunity employer and is committed to extending equal opportunity in employment to all qualified individuals without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, national or ethnic origin, physical or mental disability, marital or veteran status or any other characteristic protected by law.
Salary/Salary Range $475,000 \- $525,000, plus University provided vehicle
Additional Information
*Hofstra University provides the above salary\* as a good faith estimate of the starting pay range which considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and education. In addition to the salary offered, we offer a collegial and inclusive culture, and a benefits program which includes generous paid time off, paid holidays, tuition remission for employees and eligible dependents, and a retirement plan with University contributions.*
- *Salary ranges indicated for positions covered under a Collective Bargaining Agreement are in accordance with the CBA.*
Salary Context
This $475K-$525K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Hofstra University, 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 $166,983 based on 13,781 positions with disclosed compensation. This role's midpoint ($500K) sits 199% above the category median. Disclosed range: $475K to $525K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Hofstra University AI Hiring
Hofstra University has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Hempstead, NY, US. Compensation range: $525K - $525K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.