AI/ML Intern

Location: GTA / Toronto (remote)
Type: Internship (Unpaid)
Reports to: CTO
Website: https://www.rhineo.ca/

What You'll Do

1. Write code to add new use cases to our computer vision model - new components, wiring conditions, code violations, and safety hazards it needs to recognize and reason about.
2. Build and structure training data/scenarios for each new use case, and implement the scripts/pipelines needed to feed them into training.
3. Support model training and fine-tuning workflows for these new use cases - running experiments, tracking metrics, and iterating based on performance.
4. Work closely with our CTO to test model outputs against real jobsite scenarios and refine both the code and training data based on error patterns.
5. Build supporting tooling as needed (data ingestion, augmentation, evaluation scripts).
6. Document what's built and what's learned, so use cases can be extended and maintained over time.

What We're Looking For

• Degree/experience in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• Experience with Python and familiarity with ML/CV fundamentals.
• Comfort with YOLO - or strong eagerness to learn quickly.
• Curious and self-directed; comfortable working in a small, fast-moving startup environment with direct access to founders.
• Bonus: interest in AR/robotics/embedded systems, or exposure to skilled trades/construction.

Why Join Rhine.o
● Direct mentorship from a CTO with a background in AI research, computer
architecture (University of Toronto), and embedded ML systems (AMD, GM)
● Real ownership - your work will directly shape the models that guide technicians on
live jobsites, not a shelved side project.
● Front-row seat to building a safety-critical AI product from near-zero, including
exposure to data strategy, model development, and deployment decisions.

About Rhine.o
In Canada, 700,000 skilled tradespeople will retire by 2028, creating a critical expertise gap.
Rhine.o is an AI-powered augmented reality system that scales skilled expertise across the
workforce. Using real-time computer vision, Rhine.o renders code-compliant visual overlays,
flags safety risks, and guides technicians step-by-step through validation and pattern
detection, helping both junior and senior technicians improve first-time fix rates, standardize
execution, and reduce rework.

We're an early-stage startup building a production-grade, safety-critical system, not a
research demo. We separate perception (AI) from decision-making (deterministic rules), and
we're looking for someone who wants hands-on experience building real computer vision
systems that ship into the field.