Software Engineer, IoT

The University of British Columbia; Kelowna; On-site; CAD 6,000 - 9,000; Full time

Job summary

A leading university is seeking a Software Engineer specializing in IoT to develop a large-scale system for monitoring wildfire risks. The role involves designing and managing IoT sensors, optimizing data pipelines, and collaborating with various stakeholders to enhance fire management strategies.

Qualifications

• Minimum of one year of related experience or equivalent education.
• Willingness to respect diverse perspectives.

Responsibilities

• Develop and maintain secure, scalable data pipelines.
• Assemble, configure, and deploy custom IoT devices.
• Collaborate with wildfire scientists and agencies.

Skills

Programming

Collaboration

Problem Solving

Education

Bachelor’s degree in Engineering

Master’s degree in Computer Science

Tools

Python

C++

Java

Git

Job description

Staff - Non Union

Job Category

M&P - AAPS

Job Profile

AAPS Salaried - Scientific Eng., Level A

Job Title

Software Engineer, IoT

Department

UBCO | Research Support | Bourbonnais | Department of Earth, Environmental and Geographic Science | Irving K. Barber Faculty of Science

Compensation Range

$6,251.00 - $8,986.00 CAD Monthly

The Compensation Range is the span between the minimum and maximum base salary for a position. The midpoint of the range is approximately halfway between the minimum and the maximum and represents an employee that possesses full job knowledge, qualifications and experience for the position. In the normal course, employees will be hired, transferred or promoted between the minimum and midpoint of the salary range for a job.

Posting End Date

June 1, 2025

Note: Applications will be accepted until 11:59 PM on the Posting End Date.

Job End Date

Mar 31, 2028

At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career.

Job Summary

The Fire Ecology and Remote Sensing Lab at the University of British Columbia – Okanagan (UBCO) is seeking a specialized and motivated software engineer to support the development and deployment of a large-scale IoT system designed to monitor and predict wildfire risk and fire behaviour in real time. This system forms a critical component of a multi-institutional initiative to mitigate wildfire impacts and support proactive fire management strategies across British Columbia and beyond.

This position will help design, build, and manage a network of hundreds of remote IoT sensors that monitor key fire weather parameters. These data feed into a deep learning pipeline that integrates high-resolution satellite imagery, fuel and weather data, and state-of-the-art wildfire behavior models to generate near-real-time predictions of wildfire risk.

Organizational Status

This position reports to Dr. Mathieu Bourbonnais in the Fire Ecology and Remote Sensing Lab within the Department of Earth and Environmental Sciences, Irving K. Barber Faculty of Science.

Work Performed

• Develop and maintain secure, scalable data pipelines to ingest real-time data from a growing network of IoT weather sensors.
• Assemble, configure, and deploy custom IoT devices in field conditions, including satellite communication modules for remote data transmission.
• Optimize algorithms for edge-based preprocessing, data reduction, and anomaly detection under intermittent connectivity constraints.
• Develop and maintain a web-based dashboard for visualizing real-time sensor data, device status, and model-predicted wildfire risk.
• Integrate geospatial mapping tools (e.g., Leaflet, Mapbox, or ArcGIS APIs) for visualizing fire weather data and risk layers.
• Coordinate the integration of high-frequency satellite imagery, weather forecasts, and fire behavior model outputs (e.g., FBP, FWI) into a temporal convolutional neural network (TCN) model.
• Test, validate, and monitor system performance, ensuring reliability of devices and pipelines under rugged environmental conditions.
• Collaborate with wildfire scientists, software developers, First Nations, government, wildfire and emergency management agencies, and communities to support fire-risk modeling and adaptive decision support systems.
• Develop documentation and user training materials to support long-term system operation, troubleshooting, and field deployments.
  
  

Consequence of Error/Judgement

The software engineer is expected to exercise sound judgment and high attention to detail. Errors in system design, data handling, or model integration may lead to gaps in wildfire risk monitoring, compromise data integrity, and delay research outcomes. System reliability is essential to informing real-time fire risk mitigation and adaptive fire management strategies.

Supervision Received

The software engineer will operate independently under the general guidance of Dr. Mathieu Bourbonnais. The role requires proactive development of work plans, identification of system improvements, and accountability for project deliverables. Regular check-ins will be held to align on project milestones and review progress.

Supervision Given

May oversee or coordinate the work of technical staff, student programmers, or support personnel involved in IoT device management, deployment, or software development.

Minimum Qualifications

• Bachelor’s degree in Engineering, Computer Science, Applied Science, or a related field.
• Minimum of one year of related experience, or an equivalent combination of education and experience.
• Willingness to respect diverse perspectives, including perspectives in conflict with one’s own
• Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion
  
  

Preferred Qualifications

• Master’s degree in Computer Science, Software Engineering, or a related discipline.
• Experience with embedded systems, microcontrollers, or low-power computing (e.g., ARM, Raspberry Pi, Arduino).
• Experience with real-time operating systems (RTOS) such as FreeRTOS or Zephyr.
• Experience with cloud-based data ingestion and analytics tools.
• Proficiency in programming languages including Python, C++, and/or Java.
• Familiarity with IoT communication protocols (e.g., MQTT, LoRa, cellular/satellite telemetry).
• Understanding of version control systems (e.g., Git) and software documentation practices.
• Demonstrated ability to work independently, manage multiple tasks, and collaborate across teams.
• Experience with field-deployed IoT systems, particularly in remote or rugged conditions.
• Familiarity with wildfire behavior models (e.g., FWI, FBP) and environmental sensor data.
• Demonstrated experience developing interactive dashboards or web-based visualizations with integrated geospatial data.
• Experience integrating multispectral satellite imagery (e.g., Planet, Sentinel) into AI/ML pipelines.
• Experience in AI/ML, particularly deep learning models for temporal or geospatial data (e.g., TCN, LSTM).
• Knowledge of GIS and spatial data formats (GeoTIFF, shapefiles, KML).
• Experience with edge computing, containerization (Docker), and remote system deployment.
• Passionate about applying emerging technologies to solve urgent environmental challenges through scalable, edge-enabled, data-driven solutions.