Yale University

Lead, Geospatial Artificial Intelligence and Machine Learning

Yale University$92K — $146K *
Education, Government & Non-Profit
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in AI/ML applied to research in GeoAI and other areas.
  • Proficient in Python and/or R, along with modern computational and data management techniques.
  • Strong understanding of interdisciplinary research processes, particularly in social and environmental sciences.
  • Excellent organizational and multitasking abilities.
  • Skilled communicator with experience collaborating across diverse research teams.

Responsibilities

  • Develop and deliver user training to faculty and staff on emerging AI/ML tools.
  • Lead and support complex research projects, providing tailored solutions to researchers.
  • Manage equipment and resources within the research core, ensuring functionality and availability.
  • Contribute to developing innovative research methodologies and technologies for geospatial analysis.
  • Provide analytical insights from complex data sets, informing research decisions.
  • Stay current on emerging trends in AI/ML and represent the center at professional events.
  • Support staff growth through training and mentorship; collaborate on publications and proposals.

Benefits

  • Hybrid work model offering flexibility.
  • Opportunity to collaborate with leading experts in AI and geospatial technology.
  • Access to state-of-the-art resources and a supportive research environment.
  • Professional development opportunities through conferences and training.
  • Engagement with a diverse community and interdisciplinary projects.
Full Job Description

Overview

The Yale Center for Geospatial Solutions (YCGS) is seeking an experienced AI/ML professional to lead a new support function at the Center aimed at ensuring that Yale faculty, students, and staff can advance their geospatial work with these cutting-edge tools. As part of a new initiative at Yale, the Lead Geospatial Artificial Intelligence and Machine Learning (GAI Lead) role will strive to improve access to, and results of, AI research and applications across the social, environmental, and data sciences at Yale. To carry out this work, GAI Lead will forge connections with experts at other AI-focused units, such as the Yale Institute for Foundations and the Data Intensive Social Science Center (DISSC), to help the Yale community develop, use, and evaluate AI and apply it to deliver breakthrough research and applications at an unprecedented speed and scale.

YCGS’s mission is to provide the broad Yale community with a world class, user centered, support organization to harness emerging geospatial technologies that advance sustainability and planetary solutions. The center engages researchers and practitioners, across all disciplines to turn complex spatial data and tools into actionable insights that address pressing challenges at local to global scales. YCGS, working closely with its academic, industry, and government partners, supports the entire research lifecycle including the acquisition, secure storage and management, analysis, and dissemination of existing and novel spatial data resources transforming research from the physical and social sciences to engineering, medicine, and the humanities. YCGS also supports Yale operations and institutional decision-making, and functions as a resource and source of expertise for the greater Yale community (including the city of New Haven and the state of Connecticut).

As a key member of the YCGS team and of the Yale community carrying out this mission, the GAI Lead will be a knowledgeable AI enthusiast capable of building out a support program and of consulting with, and training faculty and staff to use emerging AI and ML tools as inputs into their work. This work will span applied GeoAI and machine learning for spatial research and applications, including remote sensing and computer vision, geospatial foundation models, LLM-enabled research workflows, API-based data and model integration, model selection, tuning, evaluation, and deployment, as well as other algorithmic methods needed to support rigorous, secure, and reproducible geospatial analysis. The AI lead must also be able to advise on public vs private models and how to work in secure environments.

The ideal candidate has experience developing or delivering research services, has a deep understanding of interdisciplinary research processes, and has skills and experience in the use of various AI and ML tools for data analysis, coding, writing and other tasks. The successful candidate will be an individual who enjoys working both independently and cooperatively with others, from a broad set of disciplinary backgrounds, on multiple projects involving a wide variety of topics and analytical tools. In this role, the GAI Lead will have principal responsibilities focused on GeoAI, generative AI, LLMs and machine learning.


Required Skills and Abilities

1. Demonstrated experience applying AI and machine learning methods to research problems, including GeoAI, generative AI, LLM-enabled workflows, computer vision, and model selection, tuning, and evaluation in interdisciplinary research settings.

2. Fluency with modern computational environments, including Python and/or R, command-line workflows, APIs, cloud or secure computing environments, and AI/ML tools, with the ability to learn and evaluate emerging methods as the field evolves.  

3. Demonstrated understanding of research methods across the social, environmental, and data sciences, with the ability to translate faculty research questions into appropriate data, modeling, evaluation, and reproducible analytical workflows.

4. Strong organizational skills, attention to detail, and ability to prioritize and manage multiple assignments simultaneously.

5. Strong interpersonal skills, communication skills, and the ability to work effectively with faculty, staff, and research partners internally and externally.

Preferred Skills and Abilities

1.Demonstrated experience applying, adapting, evaluating, and tuning GeoAI, machine learning, and Earth-observation foundation models, such as Prithvi, AlphaEarth, TerraMind, or comparable models.

2.Experience with LLM-enabled research workflows, including AI agent frameworks, and API-based model integration.

3.Understanding and appreciation of the secure use of public and private models is essential.

4.Experience teaching courses or workshops, developing technical training materials, or providing research consulting in an academic or interdisciplinary setting is a plus.

Principal Responsibilities

1. User Training: Refine training methodologies and train and mentor users of the research core, providing guidance and expertise. 2. Experiment Support: Collaborate closely with researchers and lead complex projects requiring customized solutions within the research core. 3. Facility/Instrument Support: Lead and manage research projects within the research core. 4. Technique Development: Contribute to the development of research strategies within the research core and evaluate and implement cutting-edge technologies and methodologies. 5. Data Analysis/Interpretation: Analyze and interpret complex scientific data, providing critical insights and recommendations. 6. Equipment Procurement: Assist in the evaluation, acquisition, and maintenance of research core equipment. 7. Professional Development: Stay updated with emerging research trends and technologies. Participate and present in professional development activities and scientific conferences, representing the research core at conferences and events. 8. Scientific Participation: Collaborate with users on manuscript preparation and grant proposals, as applicable. 9, Staff Training and Mentoring: Mentor and support junior staff members in their professional growth. 10. Leadership: Collaborate with senior core leadership on research core-related initiatives. 11. Finance and Admin: Support the Core Director with development and implementation of strategic plans and budgets for the research core. 12. Vendor Relations: Oversees strategic vendor partnerships, manages negotiations, and evaluates vendor performance for the research core. 13. Education and Outreach: Develop education and outreach activities within the core, including tours, events, etc..

Required Education and Experience

Master's Degree in a related discipline and five years of related experience or an equivalent combination of skills, education, and experience.

Job Posting Date

09/10/2026

Job Category

Professional

Bargaining Unit

NON

Compensation Grade

Administration & Operations

Compensation Grade Profile

Manager; Program Leader (26)

Salary Range

$92,000.00 - $146,750.00

Time Type

Full time

Duration Type

Staff

Work Model

Hybrid

Note

Yale University is a tobacco-free campus.

About Yale University

Yale University is a private Ivy League research university in New Haven, Connecticut. Founded in 1701, it is the third-oldest institution of higher education in the United States. Yale has a diverse student body and offers undergraduate and graduate degree programs in a range of academic fields. The university is known for its strong liberal arts program, as well as its professional schools of law, business, and medicine. Yale has produced numerous notable alumni, including five U.S. Presidents and 20 Nobel laureates.
Learn more about Yale University
Size
13,433 employees
Industry
Founded
1701

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