Computer Vision Engineer

About the Role

We are looking for an experienced Computer Vision / AI Lead / Solution Architect to lead the design and development of an AI-powered wildfire prevention solution for utility transmission lines in British Columbia. The ideal candidate will combine hands-on expertise in Computer Vision, Machine Learning, Predictive Analytics, and AI solution architecture with strong experience in the Energy & Utilities or Oil & Gas industry.

Key Responsibilities

• Lead the technical design, architecture, and development of an AI-powered wildfire prevention MVP.
• Develop Computer Vision and image recognition solutions to identify potential risks and hazardous conditions.
• Build predictive risk-scoring models for asset intelligence, inspection, vegetation management, and preventive maintenance.
• Design and implement scalable AI/ML solutions using Microsoft Azure technologies.
• Apply statistical modeling and Machine Learning techniques to solve complex business problems.
• Collaborate with engineering teams, business stakeholders, and client leadership to deliver AI solutions.
• Guide technical teams, communicate findings, and present recommendations to senior stakeholders.

Must-Have Skills

• 6+ years of professional experience in Data Science, Advanced Analytics, or Statistics.
• 5+ years of experience in the Energy & Utilities or Oil & Gas industry.
• Master's degree or PhD in Computer Science, Statistics, Mathematics, Economics, or a related field.
• Strong hands-on experience in Computer Vision and Image Recognition.
• Experience with predictive risk scoring, asset intelligence, asset inspection, preventive maintenance, or vegetation management.
• Proficiency in Python and R.
• Experience with Microsoft Azure AI technologies, including Azure Computer Vision, Azure Machine Learning, Microsoft Foundry, or Microsoft Fabric.
• Strong technical leadership and AI solution architecture experience.

Nice-to-Have Skills

• Experience developing wildfire prevention or vegetation management solutions.
• Knowledge of Deep Learning, NLP, sentiment analysis, topic modeling, and graph technologies.
• Experience with PyTorch, TensorFlow, Keras, NLTK, spaCy, or Neo4j.
• Familiarity with Azure AutoML, Amazon SageMaker, Databricks, DataRobot, or H2O.ai.
• Strong understanding of regression, decision trees, Random Forest, Gradient Boosting, SVM, time-series modeling, and unsupervised learning.

Interested?

If you have strong Computer Vision and AI leadership experience, particularly in the Energy & Utilities or Oil & Gas sector, we would love to hear from you.