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Job \# 042850
Department Code 20324\-6086
Department Office of Research
Job Title Project Manager, AI Institute
Location Syracuse, NY
Campus Syracuse, NY
Commitment to On\-Campus Experience
Syracuse University is committed to delivering an exceptional student experience through vibrant, engaged campus communities. This position is based at the above campus location and requires regular in\-person presence to support our students, collaborate with colleagues, and contribute to our thriving academic environment. Syracuse University values the collaboration, mentorship, and spontaneous connections that happen when our community works together on campus. Remote work arrangements are limited in accordance with University policy.
Pay Range $70,000 \- $85,000
Pay Determination
Pay rates at Syracuse University are based on a combination of factors including, but not limited to, the job responsibilities; the candidate’s education, training, work experience and key competencies; the university’s strategic priorities; internal peer equity; applicable federal, state, local laws, grant funding and contractual requisites; and external market analyses.
Staff Level S5
FLSA Status Exempt
Hours
Standard University business hours
8:30am – 5:00pm (academic year)
8:00am – 4:30pm (summer)
Hours may vary based on operational needs.
Job Type Full\-time
Unionized Position Code Not Applicable
Job Description
The AI Institute Project Manager provides centralized administrative, operational, and communications support for the AI Institute, a newly established research unit within the Office of Research at Syracuse University. Reporting to the Institute Director, the Project Manager serves as the institute’s primary administrative coordinator, responsible for day\-to\-day operations that enable faculty, staff, and researchers to focus on research and scholarship.
The Project Manager works in coordination with central university partners to ensure institute activities align with established processes and policies. Research administration coordination is performed in partnership with the Office of Sponsored Programs, Research Development, Sponsored Accounting, the Research Post\-Award team, and schools/colleges. Finance and operations are coordinated with the Office of Research Finance and Operations team and the Graduate School. Communications work is coordinated with the institute’s external marketing partner and SU’s marketing and communications teams as needed. Reporting and metrics work is coordinated with the VPR Data team.
This is a generalist role designed to provide centralized administrative capacity at launch, working in partnership with central university units that lead specialist functions.
Education and Experience
Required:* Bachelor’s degree in a relevant discipline (business, communications, public administration, or related field), or an equivalent combination of education and experience.
- Three (3\+) plus years of progressively responsible administrative, operations, or program management experience, preferably in a higher education, research, or other complex organizational setting.
Preferred:* Master’s degree. Experience supporting a research institute, center, or academic unit.
- Familiarity with sponsored research administration, university financial systems, and event coordination.
- Project Management Institute (PMI) certification (CAPM or PMP) a plus.
Skills and Knowledge
- Strong organizational and project coordination skills with the ability to manage multiple concurrent priorities under deadline pressure.
- Excellent written and verbal communication skills, including the ability to draft clear correspondence, event materials, and internal communications for varied audiences.
- Demonstrated ability to work effectively across organizational boundaries and to coordinate with multiple stakeholder offices, including faculty, central administrative units, and external partners.
- Working knowledge of university financial, procurement, and HR systems; aptitude for learning new tools quickly.
- Sound judgment, discretion, and the ability to maintain confidentiality.
- Customer\-service orientation and a collaborative working style.
- Proficiency with Microsoft Office Suite; familiarity with website content management, project management, and communications platforms preferred.
Responsibilities
- Institute Operations. Manage day\-to\-day operations of the AI Institute, including office and space coordination, calendar and scheduling support for the Director, meeting logistics, hosting visitors and partners, and maintaining institute records and internal documentation. Serve as the primary point of contact for institute administrative matters.
- Events, Programs, and Outreach Coordination. Coordinate institute events and programs, including research symposia, seminars, webinars, partner convenings, and public\-facing outreach activities. Manage end\-to\-end event logistics, including planning, vendor coordination, registration, communications, and on\-site execution. Support outreach to faculty, students, campus partners, and external stakeholders to build engagement with institute activities.
- Finance, Operations, and Institute Administration. Coordinate office operations and process institute\-level financial transactions, including procurement, reimbursements, p\-card reconciliation, and routine account monitoring, in coordination with the Office of Research Finance and Operations team.
- Support hiring and onboarding logistics, visitor coordination and logistics, and routine personnel administration for institute personnel in coordination with the Office of Research Finance and Operations and Postdoc Affairs teams.
- Coordinate graduate student researcher and assistant appointments with the Graduate School, including appointment processing, onboarding logistics, and broader graduate student coordination as needed.
- Communications. Coordinate institute communications, including website content updates, newsletters, internal announcements, and event\-related communications.
- Maintain institute\-level communications materials and support correspondence with affiliated faculty, partners, and stakeholders.
- Institutional marketing strategy and branded materials development are led by the institute’s external marketing partner and SU’s marketing and communications teams, with whom the Project Manager works in close coordination.
- Research Administration and Coordination. Serve as the institute’s primary liaison for research administration matters, coordinating pre\- and post\-award activities with campus partners on behalf of institute faculty.
- Pre\-award coordination includes deadline tracking, internal routing, and serving as the institute liaison to the Office of Sponsored Programs for proposal submission and budget preparation.
- Post\-award coordination includes routine sponsored account monitoring and serving as the institute liaison to the Office of Research Post\-Award team and the Office of Sponsored Accounting for award setup, financial reporting and monitoring, effort certification, and closeout activities. Coordinate with partnering schools and colleges as needed for joint or cross\-unit awards.
Physical Requirements
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Tools/Equipment
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Application Instructions
In addition to completing an online application, please attach a resume and cover letter.
About Syracuse University
Syracuse University is a private, international research university with distinctive academics, diversely unique offerings, and an undeniable spirit. Located in the geographic heart of New York State, with a global footprint, and over 150 years of history, Syracuse University offers a quintessential college experience.
The scope of Syracuse University is a testament to its strengths: a pioneering history dating back to 1870; a choice of more than 200 majors, 100 minors, and 200 advanced degree programs offered across the University’s 13 schools and colleges; over 15,000 undergraduates and over 6,000 graduate students; more than a quarter of a million alumni in 160 countries; and a student population from all 50 U.S. states and 123 countries. For more information, please visit http://www.syracuse.edu.
About the Syracuse area
Syracuse is a medium\-sized city situated in the geographic center of New York State approximately 250 miles northwest of New York City. The metro\-area population totals approximately 500,000\. The area offers a low cost of living and provides many social, cultural, and recreational options, including parks, museums, festivals, professional regional theater, and premier shopping venues. Syracuse and Central New York present a wide range of seasonal recreation and attractions ranging from water skiing and snow skiing, hiking in the Adirondacks, touring the historic sites, visiting wineries along the Finger Lakes, and biking on trails along the Erie Canal.
EEO Statement
Syracuse University is an equal\-opportunity institution. The University prohibits discrimination and harassment based on race, color, creed, religion, sex, gender, national origin, citizenship, ethnicity, marital status, age, disability, sexual orientation, gender identity and gender expression, veteran status, or any other status protected by applicable law to the extent prohibited by law. This nondiscrimination policy covers admissions, employment, and access to and treatment in University programs, services, and activities.
Commitment to Supporting and Hiring Veterans
Syracuse University has a long history of engaging veterans and the military\-connected community through its educational programs, community outreach, and employment programs. After World War II, Syracuse University welcomed more than 10,000 returning veterans to our campus, and those veterans literally transformed Syracuse University into the national research institution it is today. The University’s contemporary commitment to veterans builds on this historical legacy, and extends to both class\-leading initiatives focused on making an SU degree accessible and affordable to the post\-9/11 generation of veterans, and also programs designed to position Syracuse University as the employer of choice for military veterans, members of the Guard and Reserve, and military family members.
Commitment to a Respectful and Welcoming Community
Syracuse University fosters a welcoming learning environment where students, faculty, administrators, staff, curriculum, social activities, governance, and all aspects of campus life reflect a broad range of perspectives and experiences. The University community values the many similarities and differences among individuals and groups. At Syracuse, we are committed to preparing students to engage with and appreciate the richness of backgrounds, beliefs, and experiences that shape our society. To achieve this, we strive to cultivate a community that respects and encourages open dialogue, understanding, and mutual respect.
Salary Context
This $70K-$85K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Syracuse 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 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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($77K) sits 57% below the category median. Disclosed range: $70K to $85K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Syracuse University AI Hiring
Syracuse University has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Syracuse, NY, US. Compensation range: $85K - $85K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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