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Machine Learning Geospatial Jobs in Bessemer, AL

EBSCO Industries Inc

GIS Data Engineer

Birmingham, AL · Remote

Win as a Team Job Summary Moultrie is actively growing its geospatial capabilities across existing Mapbox-based mobile applications, upcoming web experiences, and support for machine learning and ...

Motorola

Senior DevOps Engineer (US REMOTE)

Birmingham, AL · Remote

$140K - $170K/yr

The solutions we create apply exciting technologies such as geospatial visualization and analytics ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in Bessemer, AL

Machine Learning Geospatial information

See Bessemer, AL salary details

$16

$26

$41

How much do machine learning geospatial jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for machine learning geospatial in Bessemer, AL is $26.04, according to ZipRecruiter salary data. Most workers in this role earn between $20.19 and $30.29 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.

Machine Learning Geospatial jobs near you

GIS Data Engineer

EBSCO Industries Inc

Birmingham, AL • Remote

Full-time

Re-posted 11 days ago

Job description

Headquartered in Birmingham, Alabama, Moultrie (www.moultrie.com) is the leader in game feeders and cellular camera innovation, building products used by hunters, property owners, and others for real-time remote monitoring.

We take pride in developing deep user understanding, obsessing about the details, and going the extra mile to show our users we love them. Moultrie is customer-driven – hardware, software, marketing, and customer success teams collaborate to deliver a quality user experience.

We are guided by the following principles: Customer Obsession.; Excellence is the Standard.; Bias for Action.; Act Boldly.; Deliver Results.; Hire and Develop the Best.; Be Curious and Learn.; Win as a Team

Job Summary

Moultrie is actively growing its geospatial capabilities across existing Mapbox-based mobile applications, upcoming web experiences, and support for machine learning and data science workflows. This role helps ensure geospatial data is identified, acquired, transformed, documented, and delivered with quality and reliability.

Job Responsibilities

Key Responsibilities

  • Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source tools.
  • Acquire, clean, transform, and load geospatial datasets to support product, engineering, and analytics use cases.
  • Execute against defined priorities and deadlines while raising risks early and communicating status clearly.
  • Perform quality assurance checks to improve data completeness, consistency, and usability.
  • Document data lineage, transformation methods, assumptions, and known gaps (for example, counties/states with missing data).
  • Contribute to repeatable geospatial processes and help improve internal GIS standards over time.
  • Support occasional off-hours on-call needs for geospatial operations.
  • Participate in interviews and provide hiring feedback when requested.

What Success Looks Like

  • Priority geospatial initiatives are delivered by agreed deadlines with clear documentation.
  • Data products are complete where possible, with clear documentation of missing or unavailable data.
  • GIS workflows are repeatable, documented, and trusted by partner teams.
  • Cross-functional teams can reliably use geospatial outputs in products, analytics, and planning.
Job Requirements

Required Qualifications

  • 3+ years of professional GIS experience.
  • Hands-on experience with QGIS, PostGIS, GDAL, Mapbox, Python, and SQL.
  • Demonstrated ability to build or support cloud hosted geospatial ETL/data preparation workflows.
  • Experience collaborating with cross-functional stakeholders and communicating technical details clearly.
  • Strong attention to detail, time management, curiosity, and ownership mindset.

Preferred Qualifications

  • 5+ years of GIS experience.
  • Experience supporting geospatial needs for product teams and/or machine learning/data science initiatives.
  • Familiarity with cloud computing in Microsoft Azure.
  • Experience with Spatiotemporal Asset Catalogs (STAC) and cloud native geospatial formats.

What We Offer

  • The funding and long-term focus of a privately-held company, combined with the energy of a startup.
  • The opportunity to work with cutting edge geospatial tools in an emerging GIS team.
  • Remote-friendly culture with an optional annual hunting trip.
Essential Job Function

We are an equal opportunity employer and comply with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, sex, pregnancy status, age, national origin or ancestry, ethnicity, religion, creed, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, training, promotion, discipline, compensation, benefits, and termination of employment.

We comply with the Americans with Disabilities Act (ADA), as amended by the ADA Amendments Act, and all applicable state or local law.

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