Senior Machine Learning Engineer II - Remote

Overview

Dandy is transforming the massive and antiquated dental industry—an industry worth over $200B. Backed by some of the world’s leading venture capital firms, we’re on an ambitious mission to simplify and modernize every function of the dental practice through technology. As we expand our reach globally, Dandy is building the operating system for dental offices around the world—empowering clinicians and their teams with technology, innovation, and world-class support to achieve more for their practices, their people, and their patients.

In Short

• Build Computer Vision models to extract structure from unstructured, information-dense 3D scans
• Research SOTA methods for developing models to accomplish 3D generative AI tasks as well as conventional computer vision tasks.
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific applications
• Develop evaluation methods which allow us to establish confidence in our datasets and models
• Implement best practices for our MLOps pipelines
• Work closely with product owners on a feature focused team to deliver value quickly to Dandy’s customers

Requirements

• 6+ years experience
• Extensive experience in Python
• Extensive experience in SOTA 2D deep learning and/or experience with 3D deep learning
• Experience with 3D geometric Computer Vision
• Experience with PyTorch
• Have immaculate attention to detail and take pride in delivering excellent code and results
• Masters or PhD in related field

Benefits

• Dandy offers a wide range of best-in-class, comprehensive, and inclusive benefits tailored to each country where we operate.
• Local benefits packages typically include healthcare, dental, mental health support, parental planning resources, retirement savings options, and generous paid time off.
• Ensuring our team members are supported no matter where they live and work.