Remote Sensing Specialist - Forest Inventory

Silvacom Group•Edmonton, AB

58d•Hybrid

About The Position

Are you passionate about leveraging the latest AI and geospatial technologies to unlock critical data-driven insights from remote sensing data? We’re looking for a Remote Sensing Specialist to join our dynamic Remote Sensing Team. In this pivotal role, you will be instrumental in pioneering the next generation of enhanced forest inventory products by transforming vast remote sensing datasets into actionable, intelligent, and scalable insights through advanced GeoAI methodologies. You'll collaborate closely with a multidisciplinary team of experts across forestry, GIS, and software development, applying innovative machine learning and deep learning techniques to help clients make informed, data-driven decisions about the land they manage. This role is ideal for an analytical mind that thrives on solving complex technical challenges, values precision, and is excited by the prospect of pushing the boundaries of geospatial AI in a team-oriented environment.

Requirements

A degree in Forestry, Geomatics, Remote Sensing, Environmental Science, Computer Science, or a related field with an emphasis on geospatial analysis and AI/ML.
Demonstrated experience in developing and deploying machine learning or deep learning models for geospatial applications, particularly with LiDAR and imagery in forested environments.
Proficiency with advanced individual tree segmentation and object detection techniques, ideally leveraging deep learning architectures.
Expertise in tools such as LAStools, lidR, PDAL, and advanced scripting languages like Python or R, with a strong command of AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Familiarity with GIS platforms (ArcGIS, QGIS) and proven experience in handling and processing large geospatial datasets for AI model training.
Strong conceptual and practical understanding of AI/machine learning techniques (e.g., supervised/unsupervised learning, deep neural networks, CNNs, Random Forest, Gradient Boosting) for forest metric prediction and classification.
Experience with cloud-based geospatial AI platforms (e.g., Google Earth Engine, Microsoft Planetary, AWS SageMaker, Azure Maps/Orbital/ML) for large-scale processing and model deployment.
Understanding of advanced remote sensing data fusion techniques, including multi-sensor and multi-temporal approaches.
Attention to detail, a strong analytical mindset, and the ability to communicate technical and GeoAI concepts clearly to diverse audiences.
A collaborative approach and comfort working in a fast-moving, multi-project setting.

Nice To Haves

Graduate-level education (MSc or PhD) is an asset, particularly in forest modeling, remote sensing, or geospatial AI.
UAV imagery and LiDAR acquisition, processing experience, and its integration in AI workflows.
Knowledge of provincial forest inventory standards and methods (e.g., Alberta, Saskatchewan, Ontario BC) and how they can be enhanced.
Understanding of how remote sensing supports forest management, planning, and decision-making.

Responsibilities

Develop and Deploy GeoAI Models: Design, develop, and validate advanced machine learning and deep learning models for precise forest inventory estimation (e.g., biomass, species classification, stand structure, growth prediction) using diverse remote sensing datasets (LiDAR, satellite imagery, UAV data).
Engineer Intelligent Workflows: Build and optimize automated workflows for efficient remote sensing data processing, feature extraction, quality control, and predictive output generation at regional and provincial scales.
Innovate with Computer Vision: Investigate and implement novel computer vision and AI algorithms for individual tree segmentation, crown delineation, change detection, and anomaly detection within complex forest environments.
Scale Geospatial Analytics: Contribute to the strategic integration and deployment of AI-driven insights into scalable platforms and client decision support systems.
Collaborate and Educate: Work closely with multidisciplinary teams, translating complex concepts and results into high-quality, client-ready deliverables.
Research & Advance: Actively research and integrate emerging tools and techniques in geospatial AI, machine learning, and deep learning to continually push the boundaries of forest inventory modeling and deliver innovative solutions.