Machine Learning Engineer

Molaris is building an AI-native operating system for the dental industry, combining workflow management with 3D dental intelligence. The Machine Learning Engineer will train, evaluate, optimize, and deploy 3D machine-learning models, while contributing to data curation, evaluation pipelines, and production ML infrastructure.

Responsibilities:

• 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