AI/Machine Learning Engineer

Position Information

About Fordham

Founded in 1841, Fordham is the Jesuit University of New York, offering an exceptional education distinguished by the Jesuit tradition to more than 16,000 students in its nine colleges and schools. It has residential campuses in the Bronx and Manhattan, a campus in West Harrison, N.Y., the Louis Calder Center Biological Field Station in Armonk, N.Y., and the London Centre in the United Kingdom.

The University offers a comprehensive benefits package that includes medical, dental, and vision insurance; flexible spending accounts; retirement plans; life insurance; short and long-term disability; employee assistance program (EAP); tuition remission; and generous time off.

Successful candidates should have a knowledge of and commitment to the goals of Jesuit Education.

Title of Position AI/Machine Learning Engineer Position Number A11100 FLSA Exempt Scheduled Hours Per Week 35 Department Enterprise AI Campus Rose Hill, Lincoln Center Work Arrangement Hybrid Hybrid Policy: Please review the Hybrid Policy at www.fordham.edu/hybridpolicy. Position Summary

Reporting to the Assistant Vice President of Enterprise AI, the AI/Machine Learning Engineer supports the advancement of the University's enterprise AI strategy by designing, building, and implementing practical artificial intelligence and machine learning solutions across the university ecosystem. This senior role serves as a technical implementation lead, contributing to a dual-path approach focused on developing targeted AI agents to support the student journey and building predictive models that help anticipate institutional needs.

Working closely with the AVP, information technology, data governance, academic, and administrative stakeholders, the role translates institutional needs into secure, scalable, ethical, and privacy-compliant AI/ML solutions that improve campus operations, decision support, and student outcomes.

Essential Functions

Designs and deploys multi-agent systems capable of reasoning, tool-use, and autonomous problem-solving throughout the student success lifecycle (Recruitment, Learning and Development, Career Services, and Alumni Relations).

Develops and maintains predictive models that provide actionable insights into areas such as student success, enrollment planning, operational efficiency, and early identification of students who may benefit from timely support.

Identifies opportunities to improve university operations and student outcomes through practical AI/ML solutions, including workflow automation, decision-support tools, and AI-assisted administrative processes.

Assists in the development of the technical roadmap for AI and machine learning implementation by assessing feasibility, documenting solution architecture, recommending scalable approaches, and supporting implementation priorities established by the AVP, with attention to ethics, privacy, security, FERPA/GDPR, and applicable governance standards.

Builds and supports retrieval-augmented generation workflows, vector database integrations, and AI application components using approved platforms, institutional data sources, and responsible development practices.

Serves as the liaison between university leadership (Administration, Deans, Faculty), technical AI/Data Science teams, and external vendors to align academic mission with technological execution.

Essential Functions Note This list is not intended to be an exhaustive list.

The University may assign additional related duties as necessary. Management Responsibilities Not responsible for supervision or oversight of others. Additional Functions

Architects AI agents using RAG (Retrieval-Augmented Generation) pipelines, Model Context Protocol, and Operational data.

Develops MLOps frameworks compliant with AI Governance policy.

Required Qualifications: Education and Experience

Master's in Computer Science, AI/Data science, Engineering, or a related field.

Minimum of 5 years of experience in Machine Learning or Data Science, with a track record of deploying predictive models in a production environment.

Required Qualifications: Knowledge and Skills

Deep proficiency in Large Language Models (LLMs) and development & deployment of autonomous AI agents (for example, leveraging LangChain and CrewAI) to move beyond simple chat interfaces into scalable, agent-driven automation.

Strong foundation in statistical modeling and classification algorithms.

Proficiency in building RAG (Retrieval-Augmented Generation) pipelines and working with vector databases.

Strong coding skills in Python and experience with MLOps frameworks to monitor model drift and performance.

Preferred Qualifications

Ph.D degree in Computer Science, Engineering, or a related field.

Minimum Starting Salary 128,000 Maximum Starting Salary 160,000 Note Salary is commensurate with qualifications, experience, and skills. Is this a Union position? No

Posting Detail Information

Posting Number A1108P Number of Vacancies 1 Start Date ASAP Posting Date 07/28/2026 Special Instructions EEO Statement

Fordham University is committed to excellence and welcomes candidates of all backgrounds.

Fordham University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.

Physical Activity and Work Environment

Physical Activity

Sitting Often Repetitive Hand Motion (such as typing) Often Hearing, Listening, Talking Often Standing Seldom Walking Seldom Running Not Required Bending, Stooping, Kneeling, squatting, Crouching, Crawling Not Required Climbing stairs Not Required Climbing ladders Not Required Reaching overhead Not Required Pulling, pushing Not Required Shoveling Not Required Lifting - up to 20 pounds Not Required Lifting - up to 50 pounds Not Required Lifting - over 50 pounds Not Required

Work Environment

Work Environment Office Environment: Employees are protected from weather conditions or contaminants, but not necessarily occasional temperature changes.