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 3 D 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. 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 East Coast, United States. Responsibilities. Collaborate with other engineers and scientists to develop scalable data pipelines for diverse AEC data sources used in production ML systems, including BIM, CAD, and infrastructure design data. 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 LL - Ms. 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 challenges. Drive technical decision-making and influence 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 5–8 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 2 D/3 D 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 deverlopment 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, or civil infrastructure design models)Exposure to AEC, infrastructure, or reality capture workflows and related platforms such as Autodesk Civil 3 D, Infra. Works, Re. Cap, or similar systems is a plus. Experience delivering production ML or data systems. Strong foundations in core computer science (data structures, algorithms, systems, and scalability)Understanding of deep learning architectures (CN - Ns, Transformers) and familiarity with frameworks such as Py. Torch. Experience building scalable data or ML pipelines in cloud environments (e.g., AWS, Sage. Maker)Experience mentoring senior engineers or leading small technical teams. Track record of driving technical innovation and engineering best practices. The Ideal Candidate. You are passionate about solving problems for AEC (Architecture, Engineering, and Construction) and infrastructure 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.