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Senior Geospatial Machine Learning Engineer

Jobgether

Remote, Canada Individual Contributor

Also open in: Remote, France, Remote, Germany, Remote, Ireland, Remote, Netherlands, Remote, Spain, Remote, Switzerland, Remote, UK

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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Canada.

Join a mission-driven, fully remote engineering team using AI, machine learning, and advanced satellite imagery to strengthen infrastructure resilience and support climate-focused outcomes. In this senior role, you will build and improve production-grade geospatial ML solutions focused on vegetation intelligence and risk detection. You will work across the full lifecycle, from data exploration and model development to deployment, monitoring, and continuous optimization. Your work will directly contribute to identifying environmental risks before they become critical operational challenges. You will collaborate with data, platform, and product teams across the Americas and Europe. The role offers significant ownership, technical depth, and the opportunity to influence how geospatial intelligence products are built and measured.

Accountabilities

    • Develop and enhance vegetation intelligence products using geospatial Python libraries, machine learning, and deep learning techniques.
    • Build, maintain, and optimize production ML models through data exploration, debugging, performance analysis, and iterative improvement.
    • Work with satellite and aerial imagery to develop computer vision and deep learning solutions that address complex geospatial challenges.
    • Lead projects end-to-end, from planning and technical execution through delivery, while clearly communicating project value and progress to cross-functional stakeholders.
    • Create measurement frameworks, evaluation tooling, and performance metrics to assess model quality and guide data-driven priorities.
    • Collaborate with upstream data ingestion teams and downstream product teams to shape scalable data pipelines, platform architecture, and product delivery.
    • Monitor production systems and investigate issues using geospatial analysis, workflow orchestration, and observability tools.
    • Contribute to continuous improvements in engineering practices, model reliability, and the effectiveness of geospatial intelligence solutions.

      • Requirements

      • 5+ years of professional experience as a Machine Learning Engineer, Data Scientist, or similar role building and deploying production machine learning or deep learning models.
      • Demonstrated experience developing computer vision or deep learning models using satellite or aerial imagery.
      • Strong proficiency in Python and geospatial libraries such as rasterio, GeoPandas, Shapely, GDAL, or equivalent technologies.
      • Hands-on experience with ML and deep learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
      • Experience with data pipeline orchestration tools such as Dagster, Airflow, dbt, or comparable workflow management platforms.
      • Familiarity with QGIS or equivalent tools for geospatial visualization and analysis.
      • Experience with model monitoring, evaluation metrics, observability, and performance measurement in production environments.
      • Strong analytical, debugging, communication, and problem-solving abilities, with the autonomy to lead projects in a distributed environment.
      • Experience with multispectral or hyperspectral satellite imagery, vegetation analysis, forestry, agriculture, or environmental monitoring is an asset.
      • Experience with tools such as Grafana, Sentry, or Prometheus and a track record of leading cross-functional initiatives are additional advantages.
      • Must be authorized to work in Canada or the country of residence without requiring visa sponsorship; sponsorship is not available for this position.

        • Benefits

        • Fully remote work arrangement, with Canada-based candidates preferred for this opportunity.
        • Opportunity to work on technology with a direct impact on infrastructure resilience, wildfire risk reduction, and climate-focused initiatives.
        • High degree of ownership across the full machine learning and geospatial product lifecycle.
        • Collaboration with a distributed, international team spanning the Americas and Europe.
        • Opportunity to work with a modern technical stack spanning Python, deep learning, geospatial analytics, data orchestration, and observability.
        • Exposure to challenging real-world applications of satellite imagery, computer vision, and environmental intelligence.
        • Cross-functional environment with opportunities to influence platform architecture, product development, and technical strategy.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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