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Machine Learning Engineer (Credit Risk) - Remote Canada
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AI Summary
Develop and deploy AI-driven 3D models for the dental industry, owning the end-to-end ML lifecycle from data curation to production deployment. Requires strong PyTorch, computer vision, and evaluation rigor for high-precision tasks. Ideal for experienced ML engineers passionate about solving complex 3D geometry and machine learning challenges.
Key Highlights
Own the end-to-end ML lifecycle for 3D models, from data to deployment.
Achieve high accuracy with sub-millimeter margins and tooth-identity precision.
Work with a modern ML/3D stack including PyTorch, geometric deep learning, and implicit representations.
Key Responsibilities
Train, optimize, and ship 3D models end to end, with senior support on architecture and deployment.
Own the problem, not just the training loop, including framing the task, curating data, choosing architecture, training, and packaging for deployment.
Hold a high accuracy bar, demanding sub-millimeter margins and tooth-identity-level precision.
Build honest evaluation by designing held-out and out-of-distribution test sets, tracking relevant metrics, and keeping scorecards trustworthy.
Help own the data backbone by curating intraoral-scan datasets, contributing to ground-truth and adjudication pipelines, and keeping provenance clean.
Work across a modern ML/3D stack including PyTorch, geometric deep learning (GNNs, point-cloud networks), multi-view CNNs, SDF and implicit representations, and foundation-model embeddings.
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Technical Skills Required
Benefits & Perks
Competitive startup salary ($110k - $150k+)
Potential equity participation
Fully flexible remote work anywhere in Canada
Health & dental benefits
Flexible vacation
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Nice to Have
Hands-on experience with 3D data (meshes, point clouds, or volumetric), or adjacent geometric and CV work.
Dental, medical, or clinical 3D-imaging experience (intraoral scans, CBCT).
Geometry processing: registration, remeshing, SDF and implicit surfaces, mesh signal processing.
Model deployment and MLOps: inference packaging, Docker, reproducible release artifacts.
Foundation models, self-supervised pretraining, or transfer learning from limited labels.
Experience presenting technical work directly to founders or executives.
Job Description
About Molaris
Molaris is building the operating system for the dental industry: the infrastructure that lets a dental operation run on AI, from case intake to finished restoration. Our founders spent years inside dental labs, working through software that tracked cases without understanding them. So we built the system they wished they'd had.
Two products, one system. ClearPath is the workflow and case-management platform an entire lab runs on. Orovia is the 3D engine that reads the clinical work moving through it.
AI-native, not AI-bolted-on. Every case processed makes the models sharper. Every feature ships to working labs, on real cases, against real deadlines.
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