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Machine Learning Geospatial Jobs (NOW HIRING)

Oxy

AI Machine Learning Engineer

Houston, TX · On-site

Work with Subject Matter Experts to design appropriate machine learning model types and ... Hands-on experience in geospatial data analytics using Esri products, with a focus on ArcGIS ...

Oxy

AI Machine Learning Engineer

Houston, TX

Work with Subject Matter Expertsto design appropriate machine learning model types and ... Handson experience in geospatial data analyticsusing Esri products, with a focus on ArcGIS ...

BlackSky

Staff SW Engineer, Machine Learning

Staff SW Engineer, Machine Learning About Us: BlackSky is a real-time intelligence company. We own ... Experience working with geospatial data and geospatial Python libraries (GDAL, shapely, rasterio ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Seeking a Geospatial Analyst to support the National Oceanic and Atmospheric Administration's (NOAA ... Knowledge or experience related to land cover classification using machine learning or more ...

ASRC Federal Holding

Geospatial Analyst

Reston, VA · On-site

... full-time Geospatial Analyst to join our DC-based team and provide agricultural and natural ... Use machine learning approaches for remote sensing and agricultural analytics * Produce maps ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Knowledge or experience related to land cover classification using machine learning or more ... sciences, geospatial analysis, information technology, resource management, conservation, and ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$112K - $154K/yr

Required Skills and Experience: * 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer. * Proven experience developing and ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

Knowledge or experience related to land cover classification using machine learning or more ... sciences, geospatial analysis, information technology, resource management, conservation, and ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

Required Skills and Experience: * 10+ years of experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer. * Proven experience developing and ...

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How much do machine learning geospatial jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for machine learning geospatial in the United States is $29.15, according to ZipRecruiter salary data. Most workers in this role earn between $22.60 and $33.89 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 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 the key skills and qualifications needed to thrive as a Machine Learning Geospatial specialist, and why are they important?

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.
More about Machine Learning Geospatial jobs
What cities are hiring for Machine Learning Geospatial jobs? Cities with the most Machine Learning Geospatial job openings:
What states have the most Machine Learning Geospatial jobs? States with the most job openings for Machine Learning Geospatial jobs include:
What job categories do people searching Machine Learning Geospatial jobs look for? The top searched job categories for Machine Learning Geospatial jobs are:
Machine Learning Geospatial jobs near you
Infographic showing various Machine Learning Geospatial job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $60,627 per year, or $29.1 per hour.

Machine Learning Engineer - Mid-Level

Voyager Technologies

El Segundo, CA • On-site

Full-time

Posted 13 days ago

Job description

Job Summary:
Voyager Technologies is an innovative defense, national security and space technology company committed to advancing transformative solutions. They are seeking a Machine Learning Engineer to develop cutting edge Deep Learning technologies for Computer Vision, Synthetic Aperture Radar (SAR), and Geospatial Exploitation, with a direct impact on U.S. government customers.
Responsibilities:
• Research, conceive, design, prototype and/or implement advanced Deep Neural Network Architectures as well as other relevant Machine Learning models
• Apply deep learning algorithms to train neural networks for object detection and classification
• Develop domain-aware pre-processing algorithms, and other methods to increase model generalization
• Apply signal pre-processing techniques on SAR data
• Create physics simulations of various phenomenologies and develop methods to account for bias between simulated and real-world data
• Develop appropriate objective functions and sound performance assessment plans
• Present work at meetings and conferences
• Develop and deliver production-quality code (mainly Python)
Qualifications:
Required:
• Must be able to obtain and maintain a US government clearance (requires US citizenship)
• 5-15 years applicable experience
• Bachelor's degree in engineering or related field
Preferred:
• Master's degree
• Strong background in Machine Learning (preferably Deep Neural Networks)
• Need to be flexible in a small business environment
• Familiarity with radar sensing phenomenology
• Open Source frameworks is a huge plus
• Ability to program in multiple languages (Python, Matlab, C/C++).
Company:
Voyager Technologies is a defense and space technology company that develops solutions for national security and commercial space missions. Founded in 2019, the company is headquartered in Denver, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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