Senior Software Engineer - AI, Building Design

Senior Software Engineer - AI, Building Design ABOUT THE JOB Here, we partner with forward-thinking organizations in the AEC (Architecture, Engineering, and Construction) industry to push the boundaries of how the built environment is designed and delivered. As the premier full-service management advisory firm exclusively focused on the built world, we combine domain expertise with leading-edge technology strategy to solve real problems at scale. We are seeking a Senior AI Engineer to lead the development of automated building design systems and advance the state-of-the-art in AI/ML applications for the built environment. You'll architect and implement generative design algorithms, computer vision systems, and optimization models that fundamentally transform how buildings are conceived, designed, and validated. This role sits at the intersection of deep learning, computational geometry, and architectural design, creating AI systems that augment human creativity while respecting engineering constraints and building codes. This is a rare opportunity to apply cutting-edge AI research to one of humanity's most fundamental challenges: creating better spaces for people to live, work, and thrive. KEY RESPONSIBILITIES - Design and implement generative AI models for automated building design, including floor plan generation, facade design, and structural optimization using state-of-the-art architectures (diffusion models, transformers, GANs). - Develop computer vision pipelines for design and drawing analysis using modern frameworks like YOLO, SAM, and NeRF-based 3D reconstruction. - Build graph neural networks and geometric deep learning models for structural analysis and MEP (Mechanical, Electrical, Plumbing) system optimization. - Create reinforcement learning systems for multi-objective building optimization (energy efficiency, cost, occupant comfort, sustainability metrics). - Integrate AI models with industry-standard BIM tools (Revit, Rhino/Grasshopper) through custom APIs and plugins. - Deploy production ML pipelines using modern MLOps practices, including experiment tracking (Weights & Biases, MLflow), model versioning, and A/B testing frameworks. - Implement physics-informed neural networks for building performance simulation and predictive modeling. - Collaborate with architects and engineers to ensure AI systems produce practical, code-compliant, and constructible designs. - Lead research initiatives and publish findings to establish us as a thought leader in AEC AI innovation. REQUIREMENTS - Master's degree or PhD in Computer Science, AI/ML, Computational Design, or related field (or equivalent industry experience). - 3-5+ years of hands-on experience building and deploying ML models in production environments. - Deep expertise with modern deep learning frameworks (PyTorch preferred). - Strong foundation in computer vision, 3D geometry processing, and spatial reasoning algorithms. - Experience with generative AI models (VAEs, GANs, Diffusion Models, Transformers) and their practical applications. - Proficiency in Python and scientific computing libraries (NumPy, SciPy, scikit-learn, Open3D, trimesh). - Experience with cloud ML platforms (AWS SageMaker, Vertex AI, or Azure ML) and distributed training frameworks. - Understanding of optimization techniques (genetic algorithms, gradient-based optimization, constraint satisfaction). - Strong software engineering practices and experience with containerization (Docker) and orchestration (Kubernetes). - Excellent communication skills to translate complex AI concepts to domain experts and stakeholders. PREFERRED QUALIFICATIONS (A PLUS, NOT A REQUIREMENT) - Experience with computational design tools (Grasshopper, Dynamo) and parametric modeling. - Familiarity with building information modeling (BIM) standards and IFC data schemas. - Knowledge of graph neural networks (PyTorch Geometric, DGL) for structural and spatial analysis. - Experience with physi ... (truncated, view full listing at source)