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Geospatial Ai Jobs in Quebec (NOW HIRING)

Flatgigs

Sales Manager

Montreal, QC

Their portfolio includes custom AI models and SDKs, GIS and geospatial intelligence, multimodal generative AI, enterprise workflow automation, AI governance, and rapid deployment solutions. Backed by ...

Flatgigs

Sales Manager

Montreal, QC · On-site

Their portfolio includes custom AI models and SDKs, GIS and geospatial intelligence, multimodal generative AI, enterprise workflow automation, AI governance, and rapid deployment solutions. Backed by ...

ALS

Geodata Scientist

Montreal, QC · Remote

... AI techniques. * Familiarity with geophysical, geological, geochemical, remote sensing, and ... Practiced in working with geospatial datasets and spatial analysis workflows. * Strong ...

All JobsGeospatial Ai JobsGeospatial Ai Jobs in Quebec

Geospatial Ai information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior data scientist, AI research director, or machine learning executive, often requiring advanced skills, extensive experience, and sometimes leadership responsibilities. These roles usually involve overseeing complex projects, developing innovative algorithms, and utilizing tools like Python, TensorFlow, or cloud platforms, with compensation reflecting the expertise and impact of the role.

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.

Will GIS jobs be taken by AI?

GIS jobs involve analyzing spatial data, and AI tools are increasingly used to automate data processing and mapping tasks. However, GIS professionals are needed for data interpretation, decision-making, and managing complex projects that require human expertise. AI complements GIS work but is unlikely to fully replace skilled GIS specialists in the near future.

What is geospatial AI?

Geospatial AI involves using artificial intelligence techniques to analyze and interpret geographic data, such as satellite imagery, maps, and spatial datasets. It is commonly used in fields like urban planning, environmental monitoring, and disaster response, often requiring skills in machine learning, GIS tools, and data analysis. Professionals in this area develop models to extract insights from spatial information to support decision-making.

Is geospatial intelligence a good career?

Geospatial intelligence is a growing field that involves analyzing geographic data using tools like GIS and remote sensing. It offers opportunities in government, defense, and private sectors, often requiring technical skills and security clearances. The career can be stable and well-paying for those with relevant expertise and certifications.

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 popular job titles related to Geospatial Ai jobs in Quebec? For Geospatial Ai jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Geospatial Ai jobs in Quebec look for? The top searched job categories for Geospatial Ai jobs in Quebec are:
Geospatial Ai jobs near you
Infographic showing various Geospatial Ai job openings in Quebec as of July 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 68% Physical, 3% Hybrid, and 29% Remote job distribution.
Ingenieur en Donnees Geospatiales / Geospatial Data Engineer

Ingenieur en Donnees Geospatiales / Geospatial Data Engineer

Shearwater

Montreal, QC • On-site

Other

Posted 17 days ago

Job description

Resume

Nous developpons un cadre d'autonomie complete qui permet aux drones de prendre des decisions de vol intelligentes a bord, sans intervention humaine. Notre plateforme combine une planification d'itineraire tenant compte de la meteo, un guidage en temps reel et une prise de decision embarquee afin de permettre aux operateurs de deployer de veritables missions autonomes capables de s'adapter aux conditions changeantes en vol.

A propos du poste

Contribuez a batir l'infrastructure de donnees pour les operations de drones autonomes. Vous travaillerez directement avec notre CTO afin de creer des systemes de traitement geospatial permettant une prise de decision de vol intelligente.

Responsabilites principales :

  • Concevoir et developper des pipelines evolutifs de traitement de donnees geospatiales et des composants logiciels.
  • Developper des outils et algorithmes d'analyse SIG pour l'optimisation des itineraires UAV.
  • Integrer et traiter des ensembles de donnees geospatiales multi-sources (elevation, obstacles, espace aerien, meteo).
  • Mettre en place des flux de travail automatises pour l'ingestion et le traitement continus des donnees.
  • Creer des API et services pour l'analyse geospatiale en temps reel.

Qualifications :

Ingenierie geospatiale :

  • 3+ annees d'experience dans le developpement de composants logiciels SIG et de systemes de traitement de donnees.
  • Maitrise des outils et bibliotheques SIG de base (QGIS, GDAL/OGR).
  • Solide comprehension des systemes de coordonnees, projections et structures de donnees spatiales.
  • Experience avec les algorithmes geospatiaux (visibilite, analyse spatiale).

Competences techniques :

  • Excellente maitrise du developpement en Python et de la pile scientifique (NumPy, Pandas, SciPy).
  • Experience avec l'ecosysteme Python geospatial (GeoPandas, Rasterio, Xarray).
  • Connaissance du SQL et des bases de donnees geospatiales (ex. : PostgreSQL/PostGIS).
  • Aisance avec les infrastructures cloud (Google Cloud de preference), les outils de conteneurisation (Docker) et le controle de version (Git).

Qualifications souhaitees

  • Diplome en SIG, informatique, ingenierie ou domaine connexe.
  • Connaissances en C/C++ pour le traitement geospatial critique en performance.
  • Experience avec les formats de donnees meteorologiques (NetCDF, GRIB) et les modeles meteo.
  • Formation ou experience en meteorologie, sciences atmospheriques ou aviation.
  • Connaissances des concepts IA/ML appliques aux donnees geospatiales (atout).

Vous avez une solide expertise en ingenierie des donnees geospatiales ? Nous voulons vous rencontrer ! Nous privilegions la capacite de resolution de problemes et l'agilite d'apprentissage plutot que la verification de toutes les cases.

Note : Seules les personnes legalement autorisees a travailler au Canada seront considerees pour ce poste.

______________

Summary

We're building a full autonomy framework that enables drones to make intelligent flight decisions onboard, without human intervention. Our platform combines weather-aware route planning, real-time guidance, and onboard decision-making to allow operators to deploy truly autonomous missions that adapt to changing conditions in flight.

About the Role

Help us build the data backbone for autonomous drone operations. You'll work directly with our CTO to create geospatial processing systems that enable intelligent flight decision-making.

Key Responsibilities

  • Design and build scalable geospatial data processing pipelines and software components
  • Develop GIS analysis tools and algorithms for UAV route optimization
  • Integrate and process multi-source geospatial datasets (elevation, obstacles, airspace, weather)
  • Build automated workflows for continuous data ingestion and processing
  • Create APIs and services for real-time geospatial analysis

Required Qualifications

Geospatial Engineering:

  • 3+ years building GIS software components and data processing systems
  • Proficiency with core GIS tools and libraries (QGIS, GDAL/OGR)
  • Strong understanding of coordinate systems, projections, and spatial data structures
  • Experience with geospatial algorithms (visibility, spatial analysis)

Technical Skills:

  • Strong Python development with scientific computing stack (NumPy, Pandas, SciPy)
  • Experience with geospatial Python ecosystem (GeoPandas, Rasterio, Xarray)
  • Familiarity with SQL and geospatial databases (e.g., PostgreSQL/PostGIS)
  • Comfortable with cloud infrastructure (Google Cloud preferred), containerization tools (Docker), and version control (Git).

Preferred Qualifications

  • Degree in GIS, Computer Science, Engineering, or related field
  • C/C++ for performance-critical geospatial processing
  • Experience with meteorological data formats (NetCDF, GRIB) and weather models
  • Background in meteorology, atmospheric science, or aviation
  • Knowledge of AI/ML concepts applied to geospatial data is a plus.

Strong foundation in geospatial data engineering? We want to hear from you! We value problem-solving ability and learning agility over checking every box.

Note: Only candidates who are legally entitled to work in Canada will be considered for this position.

Apply