Lead AI/ML Engineer

About Sidian

Sidian connects the drawings, models, documents, and decisions inside engineering firms so people and AI can work across them. We are a small Waterloo team backed by a US$1M pre-seed and working with global engineering firms.

About the role

Build vision models that read structural drawings, graph neural networks that reason over building systems, and fine-tuned language models that understand engineering intent. You will work directly with the founders and customers while owning the path from model development to production.

Responsibilities

• Build graph learning systems: GNNs over the company knowledge graph for link prediction, classification, and reasoning across connected engineering data.
• Fine-tune foundation models using LoRA, QLoRA, PEFT, instruction tuning, and evaluation harnesses that show whether a model actually improved.
• Design the algorithms underneath: shortest path, traversal, clustering, and optimization routines that power search, routing, and recommendations over graph-structured engineering data.
• Own the ML lifecycle: data curation, training infrastructure, experiment tracking, inference optimization, and monitoring in production.
• Work with customers to turn ambiguous engineering workflows into simple, dependable products.

Requirements

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