Principal Research Engineer: Infrastructure & AEC Data - Generative AI

Position Overview
Autodesk is leading the transformation of the AEC industry, integrating AI technology into ourproducts. 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 Senior or PrincipalResearch 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.
 

Report: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

• Lead and collaborate with other engineers to develop scalable data pipelines for diverseAEC data sourcesused in production ML systems

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

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

• Transform unstructured AEC data into representations suitable for machine learning

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

• Apply deduplication, normalization, and validation techniques to ensure high-qualitydatain production environments

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

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

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

• Lead initiatives to communicate findings through quantitative analysis, visuals, and clear insights

• 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

• 7-10+ 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 withmachine learningconcepts 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)

PreferredQualifications

• Experience with AEC data formats and workflows (e.g., BIM, IFC, CAD, drawing sets)

• Experience with MEP data or systems (e.g., HVAC, electrical, plumbing)

• Experience deliveringproduction 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

• You are passionate about solving problems for AEC (Architecture, Engineering, and Construction) customers by applying machine learning techniques

• You are comfortable working in newly forming ambiguous areas where learning and adaptability are key skills

• You easily collaborate with others and are comfortable with minimal direction

• You are constantly striving to learn new technologies and methodologies

• You seek new ways to solve hard problems

• You are unafraid to put your ideas out there and fail fast