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

Basic 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)

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
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

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