Senior Machine Learning Developer, 3D Geometry & Multimodal AI

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

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)