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

Job Requisition ID #

Position Overview

We are seeking a Senior Machine Learning Engineer to design, develop, and deploy machine learning solutions for next-generation AI-powered capabilities within Autodesk products. The ideal candidate has expertise across the machine learning lifecycle, including research, experimentation, data pipelines, model training, evaluation, MLOps, and production deployment.

You will work closely with researchers and engineers to develop innovative AI solutions involving 3D geometry, multimodal AI, and generative AI, helping transform research into production-ready product capabilities. You enjoy solving complex technical problems, exploring new ideas, and collaborating across teams to deliver scalable, high-quality machine learning solutions.

Responsibilities

- 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

Minimum Qualifications

- 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