Autodesk is leading the transformation of the AEC industry, integrating AI technology into our products. As a Senior Principal Research Engineer, you will help build foundation models and generative AI tools for the AEC industry, working collaboratively to enhance design and engineering workflows.
Responsibilities:
- Lead and collaborate with other engineers to develop scalable data pipelines for diverse AEC data sources used 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 design novel 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 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
- 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
- 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
Requirements:
- 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 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)
- 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 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