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Gis Machine Learning Jobs (NOW HIRING)

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene ...

EBSCO Industries Inc

GIS Data Engineer

Birmingham, AL · Remote

... for machine learning and data science workflows. This role helps ensure geospatial data is ... Support the Senior GIS Developer in building and maintaining GIS data workflows using open-source ...

Beyond SOF

GIS Data Architect/Analyst

Baton Rouge, LA · On-site

Expertise and/or relevant experience in the following areas are mandatory: • GIS data modeling o ... • Machine Learning • Deep Learning o Large Language Models • Generative Pre-training ...

The Jacobs Brand

GIS Developer

Houston, TX · On-site +1

Employ GIS and remote sensing techniques to Earth, Moon, and other planetary image data in support ... Machine learning, deep learning, neural networks * Mission science integration and operations

City of Palm Coast, FL

GIS Administrator

Palm Coast, FL · On-site

$73K - $87K/yr

Conducts ongoing R&D of emerging geospatial technologies, including AI/Machine Learning applications, 3D modeling, and remote sensing (LiDAR/Imagery) integration. * Community Outreach: Executes GIS ...

City of Palm Coast

GIS Administrator

Palm Coast, FL

$73K - $87K/yr

Conducts ongoing R&D of emerging geospatial technologies, including AI/Machine Learning applications, 3D modeling, and remote sensing (LiDAR/Imagery) integration. Community Outreach: Executes GIS ...

Field AI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene ...

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All JobsGis Machine Learning Jobs

Gis Machine Learning information

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$14

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$48

How much do gis machine learning jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for gis machine learning in the United States is $28.52, according to ZipRecruiter salary data. Most workers in this role earn between $21.63 and $33.65 per hour, depending on experience, location, and employer.

What are GIS Machine Learning jobs?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are some common challenges faced when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning Specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

More about Gis Machine Learning jobs
What cities are hiring for Gis Machine Learning jobs? Cities with the most Gis Machine Learning job openings:
What states have the most Gis Machine Learning jobs? States with the most job openings for Gis Machine Learning jobs include:
What job categories do people searching Gis Machine Learning jobs look for? The top searched job categories for Gis Machine Learning jobs are:
Gis Machine Learning jobs near you
Infographic showing various Gis Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution, with an average salary of $59,329 per year, or $28.5 per hour.
Machine Learning Engineer - Mapping

Machine Learning Engineer - Mapping

Waymo

Mountain View, CA • On-site

Other

Posted 18 days ago

Job description

The Waymo Mapping team's goal is to build a high resolution map of the world to support safe autonomous driving. We work on creating the map using a combination of automatic and manual techniques and build the infrastructure to store, process, and distribute the map. Our team collaborates with several other Waymo teams that consume map data.

In this role, you will:

  • Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps, unlocking scale for the Waymo Driver.
  • Apply and advance state-of-the-art ML techniques, including Vision-Language Models (VLMs) and other Generative AI approaches, to pioneer new solutions in mapping automation.
  • Own the complete model development lifecycle, from data mining and processing to model training, evaluation, validation, and productionization.
  • Collaborate closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to adapt cutting-edge research into scalable, reliable, and production-grade solutions.

You have:

  • 4+ years of hands-on experience in Machine Learning, with a strong focus on computer vision and/or deep learning.
  • Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
  • Demonstrated experience owning problems end-to-end and working across various parts of the systems stack to deliver results.
  • B.S. in Computer Science, a similar technical field, or equivalent practical experience.

It's a Bonus if you have:

  • M.S. or Ph.D. degree in Computer Science or a related discipline.
  • Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
  • A track record of publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
  • Experience with C++.
  • Direct experience with mapping or GIS is a bonus but not required.

Apply