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Geospatial Ai Jobs in Novato, CA (NOW HIRING)

YO AI Labs

GIS/Geospatial Expert

San Francisco, CA · Remote

$80 - $100/hr

GIS & Geospatial AI Expert Role Type: Contractor Location: Remote Job Overview We are seeking experienced GIS and Geospatial Experts to contribute their technical expertise to a project focused on ...

Pytho AI, Inc

AI Engineer

San Francisco, CA · On-site

We build AI for the most important problem in defense - making sure the force is ready to fight ... Build scalable data pipelines for structured and unstructured data (text, imagery, geospatial ...

Prologis

Lead AI Engineer

San Francisco, CA · On-site

$147K - $202K/yr

Develop multimodal data pipelines that convert BIM, Autodesk, geospatial, document, and operational data into structured, queryable knowledge. * Deliver AI workflows supporting design, construction ...

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All JobsGeospatial Ai JobsGeospatial Ai Jobs in Novato, CA

Geospatial Ai information

See Novato, CA salary details

$73.4K

$90.8K

$108.6K

How much do geospatial ai jobs pay per year?

As of Aug 30, 2026, the average yearly pay for geospatial ai in Novato, CA is $90,820.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,100.00 and $96,300.00 per year, depending on experience, location, and employer.

How do geospatial AI professionals typically collaborate with other teams to deliver actionable insights?

Geospatial AI professionals often work closely with data scientists, GIS analysts, software engineers, and domain experts to develop, validate, and deploy spatial models. Collaboration usually involves integrating spatial data with machine learning algorithms, ensuring data quality, and tailoring outputs to meet the needs of end users such as urban planners or environmental scientists. Regular meetings, shared project management tools, and cross-functional workshops are common, fostering a collaborative environment that accelerates problem-solving and innovation.

What are the key skills and qualifications needed to thrive as a geospatial AI specialist, and why are they important?

To thrive as a Geospatial AI Specialist, you need a strong background in geospatial analysis, machine learning, and programming (often with Python or R), typically supported by a degree in geography, computer science, or a related field. Familiarity with GIS platforms (such as ArcGIS or QGIS), remote sensing software, and AI/ML frameworks like TensorFlow or PyTorch is essential. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting complex data and collaborating with multidisciplinary teams. These competencies are crucial to develop innovative geospatial solutions that drive decision-making across sectors like urban planning, environmental monitoring, and logistics.

What is the difference between Geospatial Ai vs GIS Analyst?

AspectGeospatial AiGIS Analyst
Required CredentialsDegree in GIS, Computer Science, or related; experience with AI/ML toolsDegree in Geography, GIS, or related; proficiency in GIS software
Work EnvironmentTech-focused, data science teams, field data collectionOffice-based, mapping, spatial data analysis
Industry UsageTech companies, AI-driven mapping, autonomous systemsGovernment, urban planning, environmental management
Search & Comparison IntentFocus on AI applications in geospatial dataFocus on traditional spatial data analysis

Geospatial Ai combines artificial intelligence techniques with geospatial data analysis, often involving machine learning and data modeling. GIS Analysts primarily focus on mapping, spatial data management, and traditional geographic information systems. While both roles work with spatial data, Geospatial Ai emphasizes AI-driven insights, whereas GIS Analysts concentrate on spatial data visualization and analysis using GIS software.

What job categories do people searching Geospatial Ai jobs in Novato, CA look for?

The top searched job categories for Geospatial Ai jobs in Novato, CA are:

What cities near Novato, CA are hiring for Geospatial Ai jobs?

Cities near Novato, CA with the most Geospatial Ai job openings:

Geospatial Ai jobs near you
Infographic showing various Geospatial Ai job openings in Novato, CA as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $90,820 per year, or $43.7 per hour.

GIS/Geospatial Expert

YO AI Labs

San Francisco, CA • Remote

$80 - $100/hr

Full-time

Posted 4 days ago

Job description

Job Title: GIS & Geospatial AI Expert

Role Type: Contractor
Location: Remote

Job Overview

We are seeking experienced GIS and Geospatial Experts to contribute their technical expertise to a project focused on advancing next-generation AI systems. In this role, you will provide domain knowledge, document advanced technical workflows, and evaluate AI-generated solutions in real-world geospatial and STEM environments.

The ideal candidate combines strong expertise in GIS, remote sensing, spatial analytics, and Python with hands-on experience using modern AI coding agents such as Codex, Claude Code, Claude Cowork, and Claude Science.

No prior AI training experience is required. What matters most is your ability to apply AI coding agents to meaningful technical problems, explain your workflows clearly, and evaluate the quality of AI-generated solutions.

Scope of Work
  • Provide expert analysis, feedback, and practical examples related to GIS, geospatial data, remote sensing, and spatial analytics.
  • Document advanced technical workflows and problem-solving approaches involving AI coding agents such as Codex, Claude Code, Claude Cowork, and Claude Science.
  • Describe real-world tasks where AI coding agents are used to execute multi-step technical workflows rather than functioning solely as conversational tools.
  • Document project context, tool selection, technical approach, agent-generated sequences, and resulting outcomes.
  • Evaluate and critique AI-generated solutions for sophisticated geospatial challenges, including large codebase navigation, debugging, feature development, automation, and architectural changes.
  • Share real-world examples where ambiguity, scale, data complexity, or technical constraints created unique challenges and explain how AI agents contributed to solving them.
  • Use Python and relevant geospatial tools to support technical analysis and workflow development where appropriate.
  • Collaborate asynchronously with stakeholders to refine technical documentation, evaluation criteria, and guidance materials.
  • Contribute to high-fidelity datasets, evaluations, and benchmarks used for AI training and technical capability assessment.
Required Skills
  • GIS / Geospatial Analysis
  • Remote Sensing
  • Spatial Analytics
  • Python
  • AI Coding Agents
  • Technical Documentation
  • Problem-Solving
  • Analytical Thinking
  • Written and Verbal Communication
  • Stakeholder Collaboration
Preferred Qualifications
  • Demonstrated professional expertise in GIS, remote sensing, spatial analytics, geospatial engineering, or a related STEM discipline.
  • Direct hands-on experience using AI coding agents, particularly Codex, Claude Code, Claude Cowork, or Claude Science, to solve technical problems.
  • Experience applying AI agents to real-world GIS, geospatial, scientific, engineering, or other technical projects.
  • Ability to document complex technical workflows clearly for both technical and non-technical audiences.
  • Experience using AI coding agents for sophisticated tasks such as navigating large codebases, debugging, developing end-to-end features, refactoring, automation, or architectural changes.
  • Experience evaluating AI-generated code or multi-step agent workflows rather than using AI agents solely for conversational assistance.
  • Strong Python programming experience and familiarity with geospatial libraries, APIs, databases, or analytical platforms.
  • Current or recent professional engagement in a technical STEM or geospatial role.
  • Strong analytical mindset and ability to identify technical limitations, ambiguities, edge cases, and opportunities for improvement.
  • Ability to work independently in a remote environment while collaborating effectively with project stakeholders.