Lead AI/ML Engineer

Sidian Inc.; Southwestern Ontario; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

Sidian is seeking a Lead AI/ML Engineer in Waterloo, Ontario, a full-time hybrid role. You will build models such as graph neural networks to read and reason over engineering data, and fine-tune foundation models for real-world customer workflows.

You will own data curation, training infrastructure, experiment tracking, inference optimization, and production monitoring, collaborating with cross-functional teams. A master's degree is helpful but not required.

Qualifications

• Strong Python, deep learning fundamentals.
• Experience with CNNs, computer vision, GNNs, and PyTorch Geometric or DGL.
• Practical experience fine-tuning and rigorously evaluating language models.
• High agency, product judgment, and clear communication.
• Master's education is helpful but not required.

Responsibilities

• Build GNN systems for link prediction, classification, and reasoning over connected engineering data.
• Fine-tune foundation models using LoRA, QLoRA, PEFT, instruction tuning, and rigorous evaluation.
• Design graph algorithms for search, routing, and recommendation.
• Own data curation, training infrastructure, experiment tracking, inference optimization, and production monitoring.
• Turn customer workflows into dependable products.

Skills

Python

Deep learning

PyTorch

GNNs

Geometric DL

Model fine-tuning

Experiment tracking

Production monitoring

Communication

Data curation

Education

Master's degree (preferred)

Tools

PyTorch Geometric

DGL

LoRA

QLoRA

PEFT

Job description

Sidian is building the company brain for engineering firms. As Lead AI/ML Engineer, you will build the models that make that brain think: vision systems that read structural drawings, graph neural networks that reason over building systems, and fine-tuned language models that understand engineering intent.

What you will own

• Build GNN systems for link prediction, classification, and reasoning over connected engineering data.
• Fine-tune foundation models using LoRA, QLoRA, PEFT, instruction tuning, and rigorous evaluation.
• Design graph algorithms for search, routing, and recommendation.
• Own data curation, training infrastructure, experiment tracking, inference optimization, and production monitoring.
• Turn customer workflows into dependable products.

What you bring

• Strong Python, deep learning fundamentals, and end-to-end PyTorch training experience.
• Experience with CNNs, computer vision, GNNs, and geometric deep learning using PyTorch Geometric, DGL, or equivalent.
• Practical experience fine-tuning and rigorously evaluating language models.
• High agency, product judgment, and clear communication. AEC experience is not required.
• A master's education is helpful but not required.

This is a full-time, hybrid role in Waterloo, Ontario.