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Gis Machine Learning Jobs in California (NOW HIRING)

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D ... GIS systems, or structured scene representations. • Familiar with MLOps pipelines using Ray ...

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 ...

Waymo

Machine Learning Engineer - Mapping

Mountain View, CA · On-site +1

$204K - $259K/yr

Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps ... Direct experience with mapping or GIS is a bonus but not required. The expected base salary range ...

Esri

GIS Solution Engineer - AEC

Redlands, CA · On-site

Esri is a company that specializes in GIS technology, and they are seeking a GIS Solution Engineer ... machine learning concepts • Programming and scripting experience with languages such as Python ...

Esri

GIS Solution Engineer - AEC

Redlands, CA

Experience incorporating real-time information streams with existing GIS data and IT infrastructure * Basic understanding of artificial intelligence/machine learning concepts * Programming and ...

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All JobsGis Machine Learning JobsGis Machine Learning Jobs in California

Gis Machine Learning information

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.

What are popular job titles related to Gis Machine Learning jobs in California? For Gis Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Gis Machine Learning jobs in California look for? The top searched job categories for Gis Machine Learning jobs in California are:
What cities in California are hiring for Gis Machine Learning jobs? Cities in California with the most Gis Machine Learning job openings:
Gis Machine Learning jobs near you

Science and Conservation Associate

Laguna Ocean Foundation

Laguna Beach, CA • Remote

Part-time

Posted 5 days ago

New

Job description

Science and Conservation Associate

Location: Laguna Beach, California
Organization: Laguna Ocean Foundation (LOF)
Status: Part-time (Contingent upon funding)

About Laguna Ocean Foundation

The Laguna Ocean Foundation (LOF) is a nonprofit dedicated to protecting and restoring Laguna Beach’s coastal ecosystems through science, education, conservation, and community engagement. Working with universities, government agencies, and community partners, LOF is advancing innovative coastal monitoring by integrating field ecology with drones, GIS, machine learning, environmental DNA (eDNA), and citizen science.

Position Summary

LOF seeks a motivated Science and Conservation Associate to support the technical foundation of its research and conservation programs. This position transforms field observations into high-quality geospatial data that inform ecological monitoring, restoration, conservation planning, and public education across Laguna Beach’s Marine Protected Areas.

The Associate will manage geospatial workflows—from drone and underwater ROV surveys through machine-learning analysis, GIS integration, habitat mapping, and scientific visualization. Working closely with LOF biologists, university researchers, GIS specialists, and interns, the Associate will help build one of California’s most comprehensive long-term coastal spatial datasets while supporting scientific publications, grant-funded research, StoryMaps, and emerging conservation technologies.

Position contingent upon funding.

Primary Responsibilities

Remote Sensing & Field Operations

● Conduct drone surveys under FAA Part 107 regulations.

● Operate underwater ROVs to document marine habitats.

● Coordinate field logistics, equipment, permits, and data collection.

GIS & Spatial Analysis

● Process drone imagery into ortho-mosaics and elevation models.

● Maintain GIS databases and produce habitat, species, and change-detection maps.

● Integrate remote sensing with biological field data.

Artificial Intelligence & Data Science

● Develop and apply machine-learning models for habitat and species classification.

● Improve classification workflows and support Python-based geospatial automation.

Research & Communication

● Collaborate with scientists and partner institutions on applied conservation research.

● Assist with scientific publications, technical reports, grant proposals, and conference presentations.

● Develop Story-Maps, dashboards, and visual products that communicate science to diverse audiences.

Training & Program Support

● Mentor interns and volunteers in GIS, drone operations, and data collection.

● Help establish standardized monitoring and data management protocols.

Required Qualifications

● Bachelor’s degree in GIS, Geography, Environmental Science, Marine Science, Engineering, Computer Science, Data Science, Ecology, or related field (or equivalent experience).

● At least one year of experience in remote sensing, GIS, spatial analysis, or environmental monitoring.

● Proficiency with ArcGIS Pro and/or QGIS.

● Experience with Python for geospatial analysis or machine learning.

● Experience processing drone imagery using photogrammetry.

● Familiarity with image classification or computer vision workflows.

● Knowledge of geospatial data management and reproducible workflows.

● FAA Part 107 certification (or ability to obtain).

● Excellent organizational, communication, and technical writing skills.

Preferred Qualifications

● Experience in coastal or marine ecosystems.

● Underwater ROV experience.

● Familiarity with eDNA, ecological monitoring, or conservation research.

● Experience working with universities, government agencies, or nonprofits.

● Grant writing or peer-reviewed publication experience.

● Experience with ArcGIS Online, StoryMaps, Dashboards, or web GIS.

● Knowledge of TensorFlow, PyTorch, Detectron2, or similar frameworks.

● Experience with cloud-based geospatial workflows.

Please send your resume and cover letter to: Please send in your material by July 31 to info@lagunaoceanfoundation.org

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