Autodesk
Architecture, Engineering, and Construction (AEC)
PrincipalResearchEngineerAECData-GenerativeAI
Neural analysis suggests this role is
optimal for Principal candidates.
“Principal Research Engineer AEC Data - Generative AI at Autodesk. Skills: Generative AI, AEC Data, Machine Learning, Data Engineering. Develop scalable data pipelines. Design novel preprocessing”
Industry & Context.
Solve hard problems; Complex data challenges
What They're Looking For.
Must Have
MSc or PhD in Computer Science, Engineering, or related field, 5–8+ years of experience in Machine Learning, Engineering, or related fields, Proven technical leadership, Experience in geometric data modeling and processing, Familiarity with machine learning concepts and frameworks, Proficiency in Python, Proficiency in software development practices, Ability to translate research ideas into production-grade systems, Excellent communication skills, Ability to influence and guide technical decisions, Background in Architecture, Engineering, or Construction (AEC)
Nice to Have
Experience with AEC data formats and workflows, Exposure to AEC, infrastructure, or reality capture workflows, Experience delivering production ML or data systems, Foundations in core computer science, Understanding of deep learning architectures, Familiarity with frameworks such as PyTorch, Experience building scalable data or ML pipelines in cloud environments, Experience mentoring senior engineers, Experience leading small technical teams, Track record of driving technical innovation, Track record of driving engineering best practices
What You'll Do.
Develop scalable data pipelines
Design novel preprocessing
Design novel augmentation
Design novel analysis
Design novel content understanding
Transform unstructured AEC data
Transform infrastructure data
Align data formats with downstream training
Align data formats with fine-tuning LLMs
Apply deduplication techniques
Apply normalization techniques
Apply validation techniques
Architect pipelines for scalability
Optimize pipelines for scalability
Architect pipelines for reproducibility
Optimize pipelines for reproducibility
Architect pipelines for cloud deployment
Optimize pipelines for cloud deployment
Mentor junior engineers
Provide technical guidance
Drive technical decision-making
Influence best practices
Perform requirements analysis
Communicate technical insights
Contribute to agile workflows
Participate in technical planning
Participate in roadmap development
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Collaborate with engineers; Collaborate with scientists; Collaborate with ML Research Scientists; Collaborate with Engineers
Communication Scope
Quantitative analysis; Visualizations; Documentation; Technical insights
Process & Methodology
Agile workflows, Roadmap development
Full Job Description
**Job Requisition ID #** 26WD98522 **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
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