Senior Machine Learning Developer, 3D Geometry, Multimodal AI

Autodesk

Senior Machine Learning Developer creating innovative AI solutions involving 3D geometry and multimodal AI at Autodesk. Collaborating across teams to deliver scalable, high-quality machine learning solutions.

Posted 7/28/2026full-timeRemote • 🇨🇦 CanadaSenior💰 CA$123,000 - CA$180,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing machine learning models, particularly in 3D geometry and multimodal AI, while effectively managing the machine learning lifecycle from data preparation to deployment. Proficient in MLOps practices to ensure model performance and reliability in production environments.

Highest-signal resume keywords

Machine Learning Solutions DevelopmentMLOps WorkflowsDeep Learning Frameworks (PyTorch, Hugging Face)Computational Geometry and 3D DataModel Performance Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData PipelinesModel TrainingModel EvaluationGenerative AI3D GeometryComplex Data RepresentationsModel DeploymentVersion ControlAI Tools

Soft Skills

Excellent Communication Skills

Certifications & Qualifications

Bachelor’s or Master’s Degree in Computer Science, Machine Learning, Engineering

Industry Keywords

AI-Powered Product FeaturesExperimental EnvironmentsModel VersioningContinuous ImprovementTechnical Documentation

Tech Stack

Tools & technologies

PyTorch

About the role

Key responsibilities & impact

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 developers 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

Requirements

What you’ll need

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

Benefits

Comp & perks

annual cash bonuses
commissions for sales roles
stock grants
comprehensive benefits package