Machine Learning Engineer 3D Geometry & Multimodal AI Toronto, Canada

Details

• Design, develop, and optimize machine learning models for AI-powered product features involving 3D geometry, multimodal AI, and generative AI
• Build and maintain scalable data pipelines and machine learning workflows for data preparation, model training, evaluation, and inference
• Work with complex datasets and representations for model training, evaluation, and analysis
• Design and implement evaluation methodologies, benchmarks, and experiments to measure model performance, robustness, and quality
• Collaborate with researchers and engineers to transform experimental ideas into scalable, production-ready product capabilities
• Build and maintain MLOps workflows supporting model versioning, deployment, monitoring, and continuous improvement
• Analyze model performance, identify failure modes, and implement improvements to enhance model accuracy, reliability, and efficiency
• Document and present technical designs, experimental results, and findings to collaborators and leadership
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or equivalent industry experience
• 5+ years of professional experience developing machine learning solutions
• Experience working across the machine learning lifecycle, including research, data pipelines, model training, evaluation, MLOps, and production deployment
• Experience working in research or experimental environments with evolving requirements
• Proficiency with modern deep learning frameworks (e.g., PyTorch, Hugging Face)
• Experience with computational geometry and 3D data (e.g., meshes, B-Rep models)
• Experience working with complex data representations, including 2D and 3D geometry
• Experience with version control, reproducibility, and deploying machine learning models
• Hands-on experience using modern AI/GenAI tools to improve software development, experimentation, or machine learning workflows
• Excellent written and verbal communication skills
• Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related field
• Experience with LLMs or generative AI systems (e.g., fine-tuning, prompting, evaluation, or agentic workflows)
• Experience scaling machine learning training and data pipelines (e.g., using Ray or similar frameworks)
• Experience with cloud platforms and services (e.g., AWS, Azure, Google Cloud Platform)
• Knowledge of the design, manufacturing, AEC, or media & entertainment industries
• Experience with Autodesk or similar products (e.g., CAD, CAE, CAM)