Autodesk
Principal Research Engineer AEC Data - Generative AI, East Coast United States
Job Requisition ID #
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.
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 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 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 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 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 3D, InfraWorks, ReCap, 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 (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 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
At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.
Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers.Similar Jobs
What you need to know about the Boston Tech Scene
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories

.png)

