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Machine Learning Geospatial Jobs in Saint Louis, MO

CACI

Senior Data Scientist

Saint Louis, MO

$82K - $172K/yr

Apply advanced analytics and machine learning to mission problems for the National Geospatial-Intelligence Agency (NGA). Work at the intersection of data science and geospatial intelligence, turning ...

New

Esri

Data Scientist I

Saint Louis, MO · On-site

$70K - $110K/yr

Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping * Keep up to date with the latest technology ...

Bunge North America

Data Scientist

Chesterfield, MO · On-site +1

Translate complex business problems into data-driven analytics and machine learning tasks, then ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Bunge Iberica SA

Data Scientist

Chesterfield, MO · On-site

$110 - $150/hr

Translate complex business problems into data-driven analytics and machine learning tasks, then ... Experience with geospatial data analysis, remote sensing, satellite imagery processing and deep ...

Bunge

Data Scientist

Chesterfield, MO · On-site

... machine learning to analyze vast internal and external datasets. This role is crucial for ... geospatial data analysis, remote sensing, satellite imagery processing and deep learning for ...

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All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in Saint Louis, MO

Machine Learning Geospatial information

See Saint Louis, MO salary details

$18

$28

$45

How much do machine learning geospatial jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for machine learning geospatial in Saint Louis, MO is $28.34, according to ZipRecruiter salary data. Most workers in this role earn between $21.97 and $32.93 per hour, depending on experience, location, and employer.

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are popular job titles related to Machine Learning Geospatial jobs in Saint Louis, MO?

For Machine Learning Geospatial jobs in Saint Louis, MO, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in Saint Louis, MO look for?

The top searched job categories for Machine Learning Geospatial jobs in Saint Louis, MO are:

What cities near Saint Louis, MO are hiring for Machine Learning Geospatial jobs?

Cities near Saint Louis, MO with the most Machine Learning Geospatial job openings:

Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in Saint Louis, MO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $58,943 per year, or $28.3 per hour.

Machine Learning Engineer 727

Saint Louis, MO • On-site

Freedom Technology Solutions Group
See more jobs at Freedom Technology Solutions Groupexternal

Full-time

Re-posted 12 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

Apply