Computer Vision Engineer

Aptino, Inc.; British Columbia; On-site; CAD 130,000 - 190,000; Full time

Job summary

Aptino, Inc. is seeking 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 candidate will combine hands‑on expertise in Computer Vision, Machine Learning, Predictive Analytics, and AI solution architecture with strong experience in the Energy & Utilities sector.

Qualifications

• 6+ years in Data Science, analytics, or statistics.
• 5+ years in Energy & Utilities or Oil & Gas.
• MS or PhD in CS, Stats, Math, Economics, or related field.
• Hands-on experience in Computer Vision and image recognition.
• Experience with predictive risk scoring, asset intelligence, or maintenance.
• Proficiency in Python and R.
• Experience with Azure AI technologies, including Azure Computer Vision, Azure ML, Microsoft Foundry, or Microsoft Fabric.
• Strong technical leadership and AI solution architecture.

Responsibilities

• Lead the design and development of an AI-powered wildfire prevention MVP.
• Develop CV and image recognition solutions to identify risks.
• Build predictive risk scoring for asset intelligence, inspection, vegetation management, and preventive maintenance.
• Design and implement scalable AI/ML solutions using Microsoft Azure technologies.
• Apply statistical modeling and ML 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.

Skills

Data Science

Advanced Analytics

Statistics

Energy & Utilities industry

Computer Vision

Image Recognition

Predictive Analytics

Python

R

Azure AI

AI Solution Architecture

Education

MS/PhD in CS/Stats/Math

Tools

Azure AI

PyTorch

TensorFlow

Keras

Azure ML

Microsoft Foundry/Fabric

Job description

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.