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Geospatial Ai Jobs in High Ridge, MO (NOW HIRING)

Apply AI/ML techniques to enhance geospatial analysis capabilities and improve accuracy in data extraction from various sources. * Develop API-based integration solutions to improve data exchange ...

Create, update, and manage geospatial information system databases and products. * Research using ... Apply AI/ML techniques to improve georeferencing accuracy and efficiency in the GEODEC process.

Create, update, and manage geospatial information system databases and products. * Research using ... Apply AI/ML techniques to improve georeferencing accuracy and efficiency in the GEODEC process.

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Geospatial Ai information

See High Ridge, MO salary details

$57.1K

$70.6K

$84.5K

How much do geospatial ai jobs pay per year?

As of Aug 23, 2026, the average yearly pay for geospatial ai in High Ridge, MO is $70,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,200.00 and $74,900.00 per year, depending on experience, location, and employer.

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.

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 job categories do people searching Geospatial Ai jobs in High Ridge, MO look for?

The top searched job categories for Geospatial Ai jobs in High Ridge, MO are:

What cities near High Ridge, MO are hiring for Geospatial Ai jobs?

Cities near High Ridge, MO with the most Geospatial Ai job openings:

Full-time

Re-posted 5 days ago


Job description

Freedom Technology Solutions Group is seeking a Machine Learning Engineer to develop, deploy, and optimize production AI/ML capabilities supporting mission-critical geospatial and intelligence systems. You will work at the intersection of software engineering, cloud architecture, and data science to build scalable machine learning pipelines capable of operating within secure government environments.

This is a hands-on engineering position focused on moving models from research into reliable production systems.


Responsibilities:

  • Da
  • Design, train, validate, and deploy machine learning models
  • Build production inference pipelines
  • Develop feature engineering workflows
  • Optimize model performance and resource utilization
  • Implement MLOps pipelines supporting continuous integration and deployment
  • Build scalable APIs exposing AI capabilities
  • Monitor model drift and operational performance
  • Collaborate with Data Scientists and Software Engineers
  • Deploy AI workloads into AWS cloud environments
  • Support computer vision, NLP, and geospatial AI initiatives
  • Collaborate with architects, data scientists, and mission stakeholders to gather, document, and refine customer requirements, including data mapping and integration needs
  • Assist in implementing integration solutions in collaboration with development team members
  • Facilitate communication between stakeholders to ensure timely and effective requirements execution
  • Ensure activities align with established processes, standards, and mission objectives
  • Contribute to documentation of processes, procedures, integration patterns, and lessons learned


Key Technologies

  •  A
  • Python
  • PyTorch
  • TensorFlow
  • Scikit-learn
  • Hugging Face
  • MLflow
  • Docker/Podman
  • Kubernetes/EKS
  • ECS
  • Lambda
  • SageMaker
  • GitLab CI/CD
  • Linux
  • PostgreSQL/PostGIS, Aurora, Oracle (w/Spatial)
  • Redis, Elasticache
  • GDAL, Rasterio, OGR

Required Qualifications

  • Active TS/SCI clearance (eligible for CI Poly)
  • 1-3(Junior), 3-7(Journeyman), 8-11 (Senior), >12 (Principal) years of experience in software development, system integration, or technical support roles
  • Experience working directly with customers or stakeholders in a technical or mission environment
  • Strong communication and coordination skills across technical and non-technical teams
  • Experience gathering and documenting requirements
  • Ability to manage multiple tasks and priorities in a dynamic environment
  • Familiarity with Agile development practices
  • Experience using GitLab or similar tools for collaboration and tracking


Desired Qualifications

  • Experience deploying production AI systems
  • Experience with computer vision
  • Experience with large language models
  • Geospatial AI experience
  • AWS AI services
  • Experience processing satellite imagery
  • Familiarity secure data movement environments
  • Experience working with enterprise service processes such as Service+
  • Development or scripting experience (Python, JavaScript, or similar)
  • Geospatial/GIS development a plus
  • Experience with data mapping or integration workflows (using JSON or other object notation)
  • Familiarity with operational dashboards and metrics reporting
  • Experience supporting customer requirement implementation and/or system integration efforts