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University Overview
The University of Pennsylvania, the largest private employer in Philadelphia, is a world\-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News \& World Report survey. Penn has 12 highly\-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America’s Best Large Employers in 2023\.
Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.
The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.
Posted Job Title
Assistant Director, Chief AI Officers InitiativeJob Profile Title
Manager A, Student ServicesJob Description Summary
The role will work closely with the Penn Program on Opinion Research and Election Studies (PORES) and Robert A. Fox Leadership Faculty Director and Executive Director.
The Robert A. Fox Leadership Program engages and supports Penn undergraduates and recent alumni through research and service fellowships, teaching, advising and service\-learning, events and training and partnerships and special projects. The Penn Program on Opinion Research and Election Studies (PORES) is an undergraduate research program committed to high\-quality social research in the public interest on issues of national and international importance with a focus on data analytics.
The Assistant Director of the new Chief AI Officers Initiative will be responsible for day\-to\-day management of the initiative, including program management and evaluation. The role will coordinate logistics, promotion and collaboration across internal and external stakeholders.Job Description
Responsibilities:
Program Operations and Administration: Develop and maintain annual program timelines, schedules and operational plans. Assist with budget tracking, purchasing, reimbursements and vendor coordination. Coordinate travel arrangements and itineraries for visiting AI leaders participating in campus programs. Manage lodging, transportation, reimbursements and related logistics for speakers and guests. Organize student travel experience to partner cities and organizations across the country. Ensure compliance with university travel policies and risk\-management procedures.
Partner and Executive Engagement: Serve as a primary point of contact for participating Chief AI Officers and organizational partners. Coordinate onboarding, scheduling and engagement activities for AI leaders participating in the initiative. Serve as primary liason with University leadership, connecting stakeholders across departments to best serve the initiative mission. Facilitate communication between university stakeholders, students and external partners. Build and maintain relationships with industry government, and nonprofit AI leaders nationwide.
Event Planning and Management: Lead planning and execution fo approximately eight annual workshops and one signature annual conference. Coordinate event logistics including venue reservations, contracts, catering, technology needs, registration, and participant communications. Develop event schedules, briefing materials, and timeline documents. Provide on\-site event management and support before, during and after events.
Student Engagement and Experiential Learning: Support student recruitment, selection and participation in initiative programs. Coordinate and support student participation in experiential learning opportunities, including workshops, conferences, site visits, and travel\-based programs. Develop engagement strategies that connect students with AI leaders, industry partners, and career exploration opportunities. Facilitate networking, mentoring, and professional development activities that enhance student learning and workforce readiness. Collaborate with faculty, university partners, and external organizations to create meaningful, real\-world learning experiences.
Monitor Program: Continuously track initiative activities, deliverables, participation metrics and outcomes. Maintain initiative database, records and reporting systems. Track participation and outcomes to assess program impact and support continuous improvement.
Qualifications:
Required Qualifications
- Bachelor of Science, Bachelor of Arts, and 1 to 2 years of experience or equivalent combination of education and experience is required.
- Experience coordinating programs, projects, or events involving multiple stakeholders.
- Strong organizational, project management, and communication skills.
- Demonstrated ability to build collaborative relationships with internal and external partners.
- Ability to manage multiple priorities, exercise sound judgment, and work independently.
- Proficiency with Microsoft Office Suite and willingness to travel as needed.
Preferred Qualifications
- Experience supporting executive leaders, student programs, or external partnerships.
- Experience with event planning, travel coordination, and program administration.
- Interest in artificial intelligence, technology, or innovation initiatives.
Job Location \- City, State
Philadelphia, PennsylvaniaDepartment / School
School of Arts and SciencesPay Range
$58,506\.00 \- $74,000\.00 Annual Rate
Salary offers are made based on the candidate’s qualifications, experience, skills, and education as they directly relate to the requirements of the position, and in alignment with salary ranges based on external market data for the job’s level. Internal organization and peer data at Penn are also considered.
Equal Opportunity Statement
The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state or local law.
Special Requirements
Background checks may be required after a conditional job offer is made. Consideration of the background check will be tailored to the requirements of the job.
University Benefits
- Health, Life, and Flexible Spending Accounts: Penn offers comprehensive medical, prescription, behavioral health, dental, vision, and life insurance benefits to protect you and your family’s health and welfare. You can also use flexible spending accounts to pay for eligible health care and dependent care expenses with pre\-tax dollars.
- Tuition: Take advantage of Penn's exceptional tuition benefits. You, your spouse, and your dependent children can get tuition assistance here at Penn. Your dependent children are also eligible for tuition assistance at other institutions.
- Retirement: Penn offers generous retirement plans to help you save for your future. Penn’s Basic, Matching, and Supplemental retirement plans allow you to save for retirement on a pre\-tax or Roth basis. Choose from a wide variety of investment options through TIAA and Vanguard.
- Time Away from Work: Penn provides you with a substantial amount of time away from work during the course of the year. This allows you to relax, take vacations, attend to personal affairs, recover from illness or injury, spend time with family—whatever your personal needs may be.
- Long\-Term Care Insurance: In partnership with Genworth Financial, Penn offers faculty and staff (and your eligible family members) long\-term care insurance to help you cover some of the costs of long\-term care services received at home, in the community or in a nursing facility. If you apply when you’re newly hired, you won’t have to provide proof of good health or be subject to underwriting requirements. Eligible family members must always provide proof of good health and are subject to underwriting.
- Wellness and Work\-life Resources: Penn is committed to supporting our faculty and staff as they balance the competing demands of work and personal life. That’s why we offer a wide variety of programs and resources to help you care for your health, your family, and your work\-life balance.
- Professional and Personal Development: Penn provides an array of resources to help you advance yourself personally and professionally.
- University Resources: As a member of the Penn community, you have access to a wide range of University resources as well as cultural and recreational activities. Take advantage of the University’s libraries and athletic facilities, or visit our arboretum and art galleries. There’s always something going on at Penn, whether it’s a new exhibit at the Penn Museum, the latest music or theater presentation at the Annenberg Center, or the Penn Relays at Franklin Field to name just a few examples. As a member of the Penn community, you’re right in the middle of the excitement—and you and your family can enjoy many of these activities for free.
- Discounts and Special Services: From arts and entertainment to transportation and mortgages, you'll find great deals for University faculty and staff. Not only do Penn arts and cultural centers and museums offer free and discounted admission and memberships to faculty and staff. You can also enjoy substantial savings on other goods and services such as new cars from Ford and General Motors, cellular phone service plans, movie tickets, and admission to theme parks.
- Flexible Work Hours: Flexible work options offer creative approaches for completing work while promoting balance between work and personal commitments. These approaches involve use of non\-traditional work hours, locations, and/or job structures.
- Penn Home Ownership Services: Penn offers a forgivable loan for eligible employees interested in buying a home or currently residing in West Philadelphia, which can be used for closing costs or home improvements.
- Adoption Assistance: Penn will reimburse eligible employees on qualified expenses in connection with the legal adoption of an eligible child, such as travel or court fees, for up to two adoptions in your household.
*To learn more, please visit:* *https://www.hr.upenn.edu/PennHR/benefits\-pay*
Salary Context
This $58K-$74K 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 University of Pennsylvania, 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. C-Level-level AI roles across all categories have a median of $250,000. This role's midpoint ($66K) sits 69% below the category median. Disclosed range: $58K to $74K.
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.
University of Pennsylvania AI Hiring
University of Pennsylvania has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Philadelphia, PA, US. Compensation range: $74K - $105K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 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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