Ai engineer

About the Company: Magick Tech is a forward-thinking technology company specializing in Software Product Development, Mobile Applications, Saa S Solutions, e Commerce Platforms, Enterprise Systems, and System Application Development. We leverage cutting-edge technologies, including Augmented Reality (AR), Virtual Reality (VR), Artificial Intelligence (AI), Machine Learning (ML), and Data Science, to develop innovative, high-performance solutions that drive business transformation. As a part of Magick Group, Magick Tech operates alongside industry leaders like Magick Woods, one of North America’s premier manufacturers and marketers of high-quality kitchen and bath furniture. Headquartered in Toronto, Ontario, Canada, Magick Woods has a strong global presence, with manufacturing and assembly facilities in India and the U. S., supported by a robust supply chain across Mexico, China, Indonesia, Vietnam, and Europe. Position Overview: We are seeking an innovative AI Engineer with expertise in AI/ML & Computer Vision to revolutionize automated space planning and design. You will build intelligent systems that automatically generate optimal interior layouts, particularly kitchen designs, by combining computer vision, 3 D modelling, spatial reasoning, and rule-based design principles. The ideal candidate will bridge the gap between AI/ML technologies and interior design expertise to create automated design solutions. Key Responsibilities: Design Rule Engine Development : Build comprehensive rules engines for interior design constraints (work triangle optimization, ergonomic guidelines, building codes, aesthetic principles) Automated Kitchen Design : Develop systems that analyze room dimensions and automatically place cabinets, appliances, and accessories following design best practices 3 D Space Planning : Create algorithms for optimal placement of hobs, sinks, refrigerators, and storage solutions based on kitchen workflow principles Spatial Constraint Solving : Implement complex constraint optimization for furniture placement, clearance requirements, and accessibility standards Computer Vision for Space Analysis : Process room scans, floor plans, and measurements to understand spatial constraints and opportunities 3 D Asset Population : Automatically populate 3 D spaces with appropriate furniture, fixtures, and appliances from product catalogs Design Validation : Ensure generated designs meet safety codes, ergonomic standards, and functional requirements Machine Learning for Design Preferences : Build models to understand and predict user design preferences and style choices Multi-constraint Optimization : Balancing aesthetics, functionality, cost, and space utilization Real-time 3 D Visualization : Interactive systems for design preview and modification Required Technical Skills: Computer Vision & 3 D Processing Open CV Open3 D Detectron2/SAM/similar technologies Machine Learning & Deep Learning Py Torch Hugging Face Transformers Light GBM/XGBoost MLflow Data Management Required Qualifications: Bachelor's or Master's degree in Computer Science, Machine Learning, Computer Vision, or related field 3+ years of experience in computer vision and machine learning Strong programming skills in Python Experience with constraint programming and optimization problems Proven track record of building rule-based systems for complex decision-making Strong understanding of 3 D geometry, spatial relationships, and collision detection Experience with version control (Git) and collaborative development Preferred Qualifications: Ph D in Computer Vision, Machine Learning, or related field Interior Design Background : Formal training or significant experience in interior design, architecture, or space planning Experience with CAD software (Auto CAD, Sketch Up, Revit) or 3 D design tools Knowledge of kitchen and furniture industry standards and suppliers Experience with cloud platforms (AWS, GCP, Azure) for ML workloads Knowledge of containerization (Docker) and orchestration (Kubernetes) Experience with real-time 3 D rendering and visualization Familiarity with furniture/product catalog management systems Experience with generative design algorithms