Computer Vision / AI Lead & Solution Architect
About the role
Computer Vision / AI Lead & Solution Architect Duration: Approx. 2 months Location: Canada Work Mode: Remote
Job Summary Our client is looking for a hands-on Computer Vision / AI Lead and Solution Architect to lead engineering and architecture for a high-stakes AI MVP focused on risk prevention for utility transmission infrastructure. You'll act as both technical manager and architect, guiding the team while staying hands-on in designing and building scalable computer vision and machine learning solutions on the Microsoft Azure ecosystem. Working with internal and client teams, you'll turn business goals into practical AI solutions, apply deep Energy & Utilities domain knowledge in areas such as asset inspection and vegetation management, and present findings to client executives.
Key Responsibilities
- Lead engineering and solution architecture for the AI MVP, managing the team while staying hands-on.
- Design and build scalable computer vision and image recognition solutions.
- Develop predictive risk scoring and asset intelligence models to support asset inspection, preventive and condition-based maintenance, and vegetation management.
- Architect solutions on the Microsoft ecosystem, including Azure Computer Vision, Azure ML, Foundry, and Fabric.
- Work with internal and client teams to understand business goals and turn them into AI and ML solutions.
- Present findings and recommendations to client executives.
Required Qualifications
- 6+ years of professional experience as a data scientist or on advanced analytics and statistics projects.
- 5+ years of experience in the Energy & Utilities or Oil & Gas sector.
- A Master's degree or PhD in Computer Science, Statistics, Economics, Mathematics, or a related field, with hands-on use of R and Python.
- Strong expertise in computer vision and image recognition.
- Experience with predictive risk scoring, asset intelligence, asset inspection, preventive and condition-based maintenance, and vegetation management.
- Hands-on experience with the Microsoft ecosystem: Azure Computer Vision, Azure ML, Foundry, and Fabric.
- Experience in a hands-on technical leadership or management role.
- Willingness to complete a mandatory background check.
Nice to Have
- Experience building risk or hazard prevention solutions (e.g., wildfire).
- Experience with deep learning for NLP and computer vision, sentiment analysis, topic modeling, and graph theory and databases.
- Experience with data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, spaCy, or Neo4j, and modeling platforms such as Azure AutoML, SageMaker, Databricks, DataRobot, and H2O.ai.
- A strong grasp of statistical modeling techniques, including A/B testing, regression, variable selection, tree-based models (decision trees, random forests, gradient boosting), SVM, time series, unsupervised learning, and mathematical optimization.
This engagement is managed end-to-end by Querentia. Our recruiters give you honest feedback at every stage, prepare you for the interview, and support a smooth onboarding once you land the offer.