AI/Machine Learning Engineer

Fordham University Portal

Rose Hill (VA)

On-site

USD 120,000 - 180,000

Full time

14 days+
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Job summary

Fordham University Portal is seeking a senior AI/ML Engineer to design, build, and implement practical AI/ML solutions across the university. This technical lead role advances enterprise AI strategies and collaborates with AVP, IT, data governance, and academic stakeholders.

The position focuses on developing student-support agents, predictive models for enrollment and operations, and secure, privacy-preserving implementations.

Qualifications

  • Designing, building, and implementing practical artificial intelligence and machine learning solutions.
  • Technical implementation lead experience.
  • Developing targeted AI agents to support the student journey.
  • Building predictive models to anticipate institutional needs.
  • Translating institutional needs into secure, scalable, ethical, and privacy-compliant AI/ML solutions.
  • Improving campus operations, decision support, and student outcomes through AI/ML.
  • Assisting in the development of technical roadmaps for AI/ML implementation.
  • Building and supporting retrieval-augmented generation workflows.
  • Building and supporting vector database integrations.
  • Building and supporting AI application components.
  • Using approved platforms, institutional data sources, and responsible development practices.
  • Serving as a liaison between university leadership, technical teams, and external vendors.

Responsibilities

  • Designs and deploys multi-agent systems capable of reasoning, tool-use, and autonomous problem-solving throughout the student success lifecycle.
  • Develops and maintains predictive models for student success, enrollment planning, and operational efficiency.
  • Identifies opportunities to improve university operations and student outcomes through AI/ML solutions.
  • Assists in the development of the technical roadmap for AI/ML implementation with governance and privacy focus.
  • Builds and supports retrieval-augmented generation workflows and vector database integrations.

Skills

AI/ML design
Multi-agent systems
Predictive modeling
Stakeholder liaison
Ethics & privacy
Roadmap development
Technical leadership
Deployment & ops

Education

PhD in CS

Tools

Vector databases
Retrieval-augmented generation

Job description

About the position

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.

Responsibilities

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.

Requirements
  • Designing, building, and implementing practical artificial intelligence and machine learning solutions.
  • Technical implementation lead experience.
  • Developing targeted AI agents to support the student journey.
  • Building predictive models to anticipate institutional needs.
  • Translating institutional needs into secure, scalable, ethical, and privacy-compliant AI/ML solutions.
  • Improving campus operations, decision support, and student outcomes through AI/ML.
  • Designing and deploying multi-agent systems.
  • Developing and maintaining predictive models.
  • Identifying opportunities for AI/ML solutions.
  • Assisting in the development of technical roadmaps for AI/ML implementation.
  • Assessing feasibility, documenting solution architecture, recommending scalable approaches.
  • Building and supporting retrieval-augmented generation workflows.
  • Building and supporting vector database integrations.
  • Building and supporting AI application components.
  • Using approved platforms, institutional data sources, and responsible development practices.
  • Serving as a liaison between university leadership, technical teams, and external vendors.
Nice-to-haves

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

Company:

Fordham University Portal

Qualifications:
Language requirements:
Specific requirements:
Educational level:
Level of experience (years):

Senior (5+ years of experience)

Tagged as: Academia, Machine Learning, NLP, United States

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