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.
