Senior Principal Research Engineer: AEC Geometric Data - Generative AI

About the Role

In this position you will lead and collaborate on scalable data pipelines for diverse AEC data sources, mentor junior engineers, and design novel preprocessing, augmentation, and analysis techniques for large‑scale multi‑modal datasets that include text and geometry. You will transform unstructured AEC data into representations suitable for machine learning, align data formats with downstream large language model training, and ensure data quality through deduplication, normalization, and validation. • Lead development of scalable data pipelines for diverse AEC data sources used in production ML systems. • Mentor junior engineers and provide technical guidance on complex data engineering challenges. • Design novel preprocessing, augmentation, and analysis techniques for large‑scale multi‑modal datasets (text and geometry). • Transform unstructured AEC data into machine‑learning‑ready representations. • Align data formats with downstream training and fine‑tuning of large language models in collaboration with ML researchers. • Apply deduplication, normalization, and validation to ensure high‑quality production data. • Architect and optimize pipelines for scalability, reproducibility, and cloud deployment. • Drive technical decision‑making and influence engineering best practices across the team.

Key Responsibilities

• ▸data pipelines
• ▸preprocessing
• ▸data augmentation
• ▸data transformation
• ▸cloud deployment
• ▸mentorship

What You Bring

The role reports to the Machine Learning Manager on the AEC Solutions team and is based near Autodesk’s Boston, Massachusetts or Toronto, Canada offices, with hybrid‑work flexibility. Minimum qualifications include an MSc or PhD in Computer Science, Engineering, or a related field, 7‑10+ years of experience in machine learning or engineering, proven technical leadership, strong expertise in geometric data modeling and processing, proficiency in Python, and a background in AEC. Preferred qualifications add experience with BIM/IFC/CAD workflows, MEP systems, production ML systems, cloud‑based data pipelines (AWS, SageMaker), and mentoring senior engineers. The ideal candidate is passionate about solving AEC problems with machine learning, thrives in ambiguous, fast‑changing environments, collaborates readily with minimal direction, and continuously seeks to learn new technologies and methodologies. • MSc or PhD in Computer Science, Engineering, or related field. • 7‑10+ years of experience in machine learning, data engineering, or related disciplines. • Proven technical leadership on complex, cross‑functional projects. • Expertise in geometric data modeling, computational geometry, and 2D/3D representations. • Proficiency in Python and strong software engineering practices. • Familiarity with deep learning architectures (CNNs, Transformers) and frameworks such as PyTorch. • Experience with AEC data formats (BIM, IFC, CAD) and MEP systems. • Experience building scalable data or ML pipelines in cloud environments (AWS, SageMaker).

Requirements

• ▸msc/phd
• ▸7+ years
• ▸technical lead
• ▸python
• ▸pytorch
• ▸bim/ifc

Benefits

Autodesk offers a competitive compensation package that includes a U.S. base salary range of $169,000 to $302,500, annual cash bonuses, stock grants, comprehensive health and wellness benefits, and generous time‑off policies. • Comprehensive health, financial, wellness, and time‑off benefits. • Stock grants and annual cash bonuses as part of the compensation package. • Hybrid work flexibility near Boston or Toronto offices.

Work Environment

Hybrid