Senior Geospatial Machine Learning Engineer

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.

This role offers the opportunity to build advanced machine learning solutions using geospatial data and satellite imagery to address critical environmental and infrastructure challenges. You will develop and optimize production ML and deep learning models that identify vegetation-related risks and support more resilient infrastructure. The position combines machine learning engineering, computer vision, geospatial analytics, and large-scale data pipelines. You will own projects end-to-end, from technical planning and experimentation through deployment, measurement, and continuous improvement. Working with distributed teams across the Americas and Europe, you will collaborate closely with data ingestion, product, and engineering teams. Your work will directly contribute to data-driven climate resilience initiatives and measurable real-world impact. The role is ideal for an experienced ML professional who enjoys complex geospatial problems, technical ownership, and mission-driven innovation.

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Accountabilities

• Develop and deploy new geospatial intelligence products using Python, machine learning, deep learning, and satellite or aerial imagery.

• Build and improve computer vision and machine learning models designed to analyze vegetation and other geospatial patterns.

• Explore geospatial datasets, identify opportunities for model improvement, debug production issues, and optimize existing ML products.

• Work with geospatial analysis and visualization tools such as QGIS and Python-based geospatial libraries.

• Lead machine learning projects from initial planning and experimentation through implementation, delivery, and ongoing optimization.

• Build measurement frameworks, evaluation tooling, and performance metrics to assess model quality and guide data-driven product decisions.

• Monitor production models and investigate performance issues using observability and monitoring platforms.

• Collaborate with upstream data ingestion teams to influence data pipelines, architecture, and processing requirements.

• Partner with downstream product and engineering teams to ensure ML solutions can be reliably integrated into production products.

• Communicate technical findings, project progress, model performance, and business impact clearly to cross-functional stakeholders.

• Contribute to scalable workflows and data pipelines using orchestration technologies such as Dagster, Airflow, or dbt.

• Continuously improve existing solutions through experimentation, model optimization, data analysis, and production feedback.

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 experience with ML and deep learning frameworks such as PyTorch, TensorFlow, and scikit-learn.

• Strong knowledge of geospatial Python libraries, including tools such as rasterio, GeoPandas, Shapely, GDAL, or equivalent technologies.

• Experience working with geospatial data formats and satellite or aerial imagery datasets.

• Experience building, managing, or contributing to production data pipelines and workflow orchestration using Dagster, Airflow, dbt, or similar tools.

• Experience with QGIS or equivalent geospatial visualization and analysis software.

• Strong understanding of model evaluation, performance metrics, monitoring, and production ML operations.

• Ability to investigate complex technical problems, optimize models, and make data-driven engineering decisions.

• Strong project ownership skills, with the ability to lead initiatives from planning through delivery.

• Excellent written and verbal communication skills and the ability to explain complex technical concepts to cross-functional stakeholders.

• Experience working effectively with distributed teams across multiple time zones.

• Experience with multispectral or hyperspectral satellite imagery is a plus.

• Background in vegetation analysis, forestry, agriculture, environmental monitoring, climate technology, or related domains is desirable.

• Familiarity with Grafana, Sentry, Prometheus, or similar monitoring and observability tools is an advantage.

• Demonstrated experience leading cross-functional technical projects is preferred.

• Must be legally authorized to work in your country of residence; visa sponsorship is not available for this position.

Benefits

• Fully remote position based in Canada.

• Opportunity to work with a distributed team across the Americas and Europe.

• Meaningful opportunity to apply machine learning and satellite imagery to climate resilience and infrastructure challenges.

• High level of technical ownership across the full ML product lifecycle.

• Exposure to advanced geospatial, computer vision, deep learning, and production ML technologies.

• Opportunity to work with a modern technology stack including Python, PyTorch, TensorFlow, GDAL, GeoPandas, QGIS, Dagster, Grafana, Sentry, and Prometheus.

• Collaborative environment with close interaction across data, engineering, and product teams.

• Opportunity to lead impactful technical initiatives from concept through production delivery.

• Mission-driven work focused on preventing environmental and infrastructure risks through technology.

• Fully distributed working environment designed to support collaboration across multiple regions.

\nHow 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?

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