Computer Vision / Machine Learning Engineer - Remote

Overview

Canvas is at the forefront of revolutionizing the remodeling, architecture and interior design industry through cutting-edge AI and computer vision technology. With our LiDAR-enabled iPhone or iPad scans, we capture precise 3D representations of homes in minutes, providing interactive models with accurate-to-the-inch measurements. Our proprietary process then turns these scans into highly detailed, editable, as-built files in industry-standard formats. Our technology was featured in Apple's keynote when the iPhone's LiDAR sensor was introduced and now we model millions of square feet each month.

We’re an early-stage startup that is growing and ready to accelerate even further. As a global virtual-first company, our team members are distributed worldwide, with a concentration in the US and Europe.

In Short

• Join our core innovation team as a Computer Vision / Machine Learning Engineer.
• Leverage a unique dataset of scans and CAD models for process automation.
• Mix of research and engineering: from papers review to production deployments.
• Develop new algorithms and train neural networks for Scan-to-CAD conversion.
• Collaborate with teams to improve efficiency of manual conversion processes.
• Improve ML infrastructure by setting up efficient data pipelines.
• Work across multiple time zones and cultures.
• Strong communication skills required.
• Experience with Python and PyTorch is essential.
• Nice to have: MS or PhD in machine learning or computer vision.

Requirements

• Deep expertise in modern machine learning techniques in computer vision.
• Rapid iteration and experimentation skills.
• Strong skills in reviewing research literature.
• Good knowledge of Python and PyTorch.
• Strong communication skills, fluent English.
• Comfortable working across multiple time zones and cultures.

Benefits

• Opportunity to generate tremendous business impact.
• Work in a global virtual-first company.
• Be part of an early-stage startup with growth potential.
• Collaborate with a diverse team.
• Engage in cutting-edge technology and research.