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Geospatial Ai Jobs (NOW HIRING)

Maxar Technologies, Inc.

Applied AI Scientist

Herndon, VA · On-site

$146K - $244K/yr

Design, develop, and deploy AI-driven applications that transform large-scale geospatial data into actionable insights and predictive intelligence. * Build and operate end-to-end AI/ML pipelines ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site +1

Own and architect the mission-aligned roadmap for geospatial CV and applied AI, partnering with customers to translate mission requirements into technical designs and implementing core components.

Urban SDK

Account Manager

Jacksonville, FL · On-site

We are pioneers in geospatial AI technology, providing public leaders with insights and automation for mission-critical decisions. We equip critical public services with geospatial AI, enabling ...

Urban SDK

Sales Engineer

Jacksonville, FL · On-site

We are pioneers in geospatial AI technology, providing public leaders with insights and automation for mission-critical decisions. We equip critical public services with geospatial AI, enabling ...

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Geospatial Ai information

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$62.5K

$77.4K

$92.5K

How much do geospatial ai jobs pay per year?

As of Jun 29, 2026, the average yearly pay for geospatial ai in the United States is $77,355.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,500.00 and $82,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Geospatial AI Specialist, and why are they important?

To thrive as a Geospatial AI Specialist, you need a strong background in geospatial analysis, machine learning, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Familiarity with GIS platforms (such as ArcGIS or QGIS), remote sensing software, and AI/ML frameworks like TensorFlow or PyTorch is essential. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting complex data and collaborating with multidisciplinary teams. These competencies are crucial to develop innovative geospatial solutions that drive decision-making across sectors like urban planning, environmental monitoring, and logistics.

What is the difference between Geospatial Ai vs GIS Analyst?

AspectGeospatial AiGIS Analyst
Required CredentialsDegree in GIS, Computer Science, or related; experience with AI/ML toolsDegree in Geography, GIS, or related; proficiency in GIS software
Work EnvironmentTech-focused, data science teams, field data collectionOffice-based, mapping, spatial data analysis
Industry UsageTech companies, AI-driven mapping, autonomous systemsGovernment, urban planning, environmental management
Search & Comparison IntentFocus on AI applications in geospatial dataFocus on traditional spatial data analysis

Geospatial Ai combines artificial intelligence techniques with geospatial data analysis, often involving machine learning and data modeling. GIS Analysts primarily focus on mapping, spatial data management, and traditional geographic information systems. While both roles work with spatial data, Geospatial Ai emphasizes AI-driven insights, whereas GIS Analysts concentrate on spatial data visualization and analysis using GIS software.

What is Geospatial AI?

Geospatial AI refers to the integration of artificial intelligence techniques with geospatial data, such as maps, satellite imagery, and location-based information. Professionals in this field use machine learning and deep learning algorithms to analyze spatial data, uncover patterns, and make predictions related to geography, urban planning, agriculture, and more. Geospatial AI is widely used for applications like disaster response, environmental monitoring, smart cities, and autonomous vehicles. It requires expertise in both AI methodologies and geographic information systems (GIS).

How do Geospatial AI professionals typically collaborate with other teams to deliver actionable insights?

Geospatial AI professionals often work closely with data scientists, GIS analysts, software engineers, and domain experts to develop, validate, and deploy spatial models. Collaboration usually involves integrating spatial data with machine learning algorithms, ensuring data quality, and tailoring outputs to meet the needs of end users such as urban planners or environmental scientists. Regular meetings, shared project management tools, and cross-functional workshops are common, fostering a collaborative environment that accelerates problem-solving and innovation.
More about Geospatial Ai jobs
What cities are hiring for Geospatial Ai jobs? Cities with the most Geospatial Ai job openings:
What states have the most Geospatial Ai jobs? States with the most job openings for Geospatial Ai jobs include:
What job categories do people searching Geospatial Ai jobs look for? The top searched job categories for Geospatial Ai jobs are:
Geospatial Ai jobs near you
Infographic showing various Geospatial Ai job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $77,355 per year, or $37.2 per hour.
POSTDOCTORAL RESEARCHER - Epidemiology & Health Data Science and Biostatistics - Luan Lab [Req#: 934

POSTDOCTORAL RESEARCHER - Epidemiology & Health Data Science and Biostatistics - Luan Lab [Req#: 934

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Posted 9 days ago

Key responsibilities

  • Train and fine-tune LLMs and GeoAI models for geospatial health data analysis.

  • Develop an LLM-based spatial analysis tool and assess its acceptability and feasibility.

  • Collaborate with experts in epidemiology, health data science, and computer science.

UT Southwestern rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

105th of 877 rated healthcare providers

Job description

Description
POSTDOCTORAL RESEARCHER - We invite applications for a Postdoctoral Researcher position focused on applying LLMs and GeoAI in geospatial health data analysis. This position will involve training and fine-tuning LLMs and GeoAI models to analyze geospatial health datasets on different topics (e.g., HIV, cardiology, and cancer) from various data sources (e.g., longitudinal health surveys, Electronic Health Record, open data). The successful candidate will also help develop an LLM-based spatial analysis tool, promote its use by public health researchers and practitioners, and assess the tool's acceptability and feasibility.
Description of Duties and Responsibilities:
• Train and fine-turning LLMs and GeoAI models for geospatial health data analysis.
• Develop an LLM-based spatial analysis tool and assess its acceptability and feasibility.
• Collaborate with experts in epidemiology, health data science, and computer science.
• Prepare manuscripts for peer-reviewed journals.
• Present research at academic conferences.
• Assist and develop new grant proposals on related topics for submission to funding agencies.
• Mentor graduate students in the research team.
Term: One year with potential extension based on performance and funding availability
Visa sponorship: J-1 if needed
Qualifications
Required Qualifications:
• A Ph.D. in Computer Science, Health Informatics, Geospatial Data Science, Statistics, or a related field.
• Strong background in (geospatial) AI and generative AI/LLM.
• Strong R or Python programming skills.
• Proven ability to publish in high-impact academic journals.
• Strong written and oral communication skills.
Desired Qualifications
• Experience with GeoAI applications in Street View Images and Remote Sensing
• Knowledge of (Bayesian) spatial statistics, spatial accessibility, and spatial optimization
• Knowledge of spatial epidemiology
Application Instructions
Interested individuals must upload a CV, cover letter, and a list of three references.

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