Principal Research Engineer: Infrastructure

Position Overview

Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. We're enhancing our applications with cloud-native capabilities, including data at scale, edge computing, AI-based solutions, and advanced 3D modeling and graphics. This innovation is happening across our flagship products—AutoCAD, Revit, and Construction Cloud—and Forma, our new Industry Cloud.

As a Principal Research Engineer, on the AEC Solutions team, you will join a team of technologists to help build foundation models and generative AI tools for the AEC industry. You will work collaboratively to create and interpret design data that can enhance design and engineering workflows.

You will report to the Machine Learning Manager in the Architecture, Engineering, and Construction (AEC) Solutions Team.

Location: We support hybrid work, and you work near our Boston, Massachusetts or Toronto, Canada offices.

Responsibilities

Collaborate with other engineers to develop scalable data pipelines for diverse AEC and infrastructure data sources used in production ML systems, including BIM models, CAD drawings, infrastructure and transportation design data

Work with large-scale infrastructure datasets—such as transportation networks, terrain models, and reality capture data—to enable machine learning workflows for infrastructure planning and engineering

Work with large-scale, multi-modal datasets including text and geometric data, to design novel preprocessing, augmentation, analysis and content understanding

Transform unstructured AEC and infrastructure data into representations suitable for machine learning

Lead cross-functional collaboration with ML Research Scientists and Engineers to align data formats with downstream training and fine-tuning of LLMs

Apply deduplication, normalization, and validation techniques to ensure high-quality data in production environments

Architect and optimize pipelines for scalability, reproducibility, and cloud deployment

Mentor junior engineers and provide technical guidance on complex data engineering challenges

Drive technical decision-making and influence engineering best practices across the team

Perform requirements analysis with senior stakeholders, ensuring technical solutions meet both immediate project goals and long-term research objectives

Communicate findings and technical insights through quantitative analysis, visualizations, and clear documentation

Contribute to agile workflows, ensuring flexibility and responsiveness to evolving project needs

Participate in technical planning and roadmap development

Minimum Qualifications

MSc or PhD in Computer Science, Engineering, or a related field

7+ years of experience in Machine Learning, Engineering, or related fields

Proven technical leadership, including leading complex projects and influencing technical direction in cross-functional teams

Strong experience in geometric data modeling and processing, including complex 2D/3D representations, computational geometry, and data architectures

Familiarity with machine learning concepts and frameworks and how data is represented for training

Proficiency in Python and strong software engineering practices

Ability to translate research ideas into production-grade systems

Excellent communication skills with ability to influence and guide technical decisions

Background in Architecture, Engineering, or Construction (AEC)

Preferred Qualifications

Experience with AEC data formats and workflows (e.g., BIM, IFC, CAD, and infrastructure or transportation design models)

Experience working with infrastructure or transportation design tools such as Autodesk Civil 3D, InfraWorks, or similar systems

Experience working with reality capture data, including point clouds or LiDAR datasets (e.g., Autodesk ReCap)

Experience delivering production ML or data systems

Strong foundations in core computer science (algorithms, systems, scalability)

Understanding of deep learning architectures (CNNs, Transformers) and familiarity with frameworks such as PyTorch

Experience building scalable data or ML pipelines in cloud environments (e.g., AWS, SageMaker)

Experience mentoring senior engineers or leading small technical teams

Track record of driving technical innovation and best practices

The Ideal Candidate

Is passionate about solving problems for AEC (Architecture, Engineering, and Construction) and infrastructure cus