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Job Description
Note: This is a Hybrid role with 4 days of on-site work and 1 day of WFH work. Please apply ONLY if you're able to commute/work on-site in Cambridge, ON, four days a week.
THE ROLE
We’re looking for a hands-on AI Engineer who excels at turning messy, raw operational data into actionable predictive models. Ideally someone who thrives on Exploratory Data Analysis (EDA), smart feature engineering, and building simple, effective end-to-end prediction models that deliver real business value. You’ll work closely with operational data that is often unclean, incomplete, or unstructured — and turn it into reliable forecasts, risk predictions, anomaly detection, or optimization models.
Key Responsibilities:
- Perform deep exploratory data analysis on raw operational datasets
- Identify patterns, clean data, and create high-impact features
- Build, validate, and deploy end-to-end predictive models (classification, regression, time-series, etc.)
- Own the full modeling lifecycle: from raw data ingestion to production model
- Collaborate with other software engineers to integrate models into our core Java/Angular platform
- Continuously monitor and improve model performance in production
Must-Have Skills:
Core Engineering
- Java, Spring Boot, REST APIs, Microservices
- Angular, TypeScript, HTML, CSS
- SQL (PostgreSQL / MySQL)
- Docker, Jenkins, Git, CI/CD
AI / Data Engineering
- Python for data analysis & ML
- Machine Learning, Predictive Analytics, Computer Vision
- ETL & streaming pipelines (Kafka, Redis, event-driven systems)
Nice to Have
- Manufacturing, logistics, or industrial systems experience
- Time-series forecasting, anomaly detection, optimization
- Hybrid mobile dev (Cordova / Android)
- Industrial protocols: MQTT, TCP/IP, PLC, OPC
About VectorVue
VectorVue
vectorvue.com
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