Position: Machine Learning Engineer (multiple positions)

Location: Canada - Fully-remote

Type: Full-time (Must be Canadian Citizen)

About Molaris

Molaris is building the Intelligent Operating System for the Dental Industry.

Our mission: building the infrastructure for scalable, AI-driven dental operations, where every dental operation runs on AI.We were founded by people who spent years inside dental labs, navigating broken workflows and software that tracked work without understanding it.

Our two products work as one system: ClearPath, the workflow and case management platform an entire operation runs on, and Orovia, the 3D software that powers our AI suite reading the clinical work moving through it. We're AI-native, not AI-bolted-on: every case processed makes the system sharper, and every feature is exercised in working labs, on real cases, against real deadlines.We're a small, fully remote team solving hard problems in 3D geometry, machine learning, and production software.

What you'll do:

- Train, optimize and ship 3D models end to end, with senior support on the trickiest architecture and deployment calls.
- Own the problem, not just the training loop. Help frame the task, curate the labeled data, choose the architecture, train it, and package it for deployment.
- Hold a high accuracy bar. These problems demand sub-millimeter margins and tooth-identity-level precision. You will learn to tell the difference between a real gain and noise.
- Build honest evaluation. Design held-out and out-of-distribution test sets, track the metrics that matter (per-tooth accuracy, margin error in millimeters, ROC), and keep the scorecards trustworthy.
- Help own the data backbone. Curate large intraoral-scan datasets, contribute to ground-truth and adjudication pipelines, and keep provenance clean.
- Work across a modern ML/3D stack. PyTorch, geometric deep learning (GNNs, point-cloud networks), multi-view CNNs, SDF and implicit representations, and foundation-model embeddings.





What we're looking for:

- 3+ years in applied ML or deep learning, with at least one model you took beyond a prototype toward production.
- Background in Mathematics or Machine learning
- Strong PyTorch fluency and solid computer-vision and deep-learning foundations.
- Evaluation rigor. You design honest tests, care about generalization and out-of-distribution behavior, and are learning to separate signal from noise reliably.
- Comfort taking ownership of well-scoped problems and driving them to a shipped result, with mentorship and code review available when you need it.
- Explicit communication. You can explain a modeling decision, its tradeoffs, and its limits.

You do not need a dental or medical background. That part is learnable, and we will teach it; depth in 3D machine learning is a plus. Strong 3D or geometric CV work from another domain (robotics, VR/AR, medical imaging) carries over.

Nice to have:

- Hands-on experience with 3D data (meshes, point clouds, or volumetric), or adjacent geometric and CV work you can carry over.
- 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.

How We Work:

Remote-first and asynchronous. A short path from idea to production, real ownership of the models you build, and direct access to the person setting technical direction. We keep the team small and the standard high.

What We Offer:

- Competitive startup salary and equity participation ($110k-$150k).
- Fully flexible remote work within Canada.
- Ownership of production 3D ML, built on a large and growing proprietary dataset.
- A modern stack and a team working at the intersection of dentistry and applied AI.

📌 Machine Learning Engineer (Canada)
🏢 Molaris AI Innovations
📍 Canada