Principal Research Engineer, AEC Data – Generative AI
Boston, Maryland, United States of America
Full Time
1 week ago
No Visa Sponsorship
Key skills
CloudPythonMachine LearningMLAgileLeadershipCommunicationCollaborationRemote Work
About this role
Role Overview
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
Requirements
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 development practices
Excellent communication skills with ability to influence and guide technical decisions
Background in Architecture, Engineering, or Construction (AEC)