Senior Software Engineer – AI, Building Design
KP Reddy
full-time
Posted on:
Location Type: Hybrid
Location: Atlanta • United States
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Job Level
About the role
- 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.
Benefits
- The opportunity to define and build AI systems that will reshape a $10 trillion global industry.
- Access to unique datasets and real-world problems at the intersection of AI and the built environment.
- Collaboration with leading architects, engineers, and construction professionals who are eager to embrace AI transformation.
- Resources to pursue cutting-edge research while maintaining a focus on practical, deployable solutions.
- Mentorship from industry veterans who understand both the technical and business aspects of AEC technology.
- The freedom to experiment with emerging AI architectures and techniques in a high-impact domain.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
generative AI modelscomputer visiondeep learning frameworksreinforcement learninggraph neural networksgeometric deep learningphysics-informed neural networksoptimization techniquesPythonspatial reasoning algorithms
Soft Skills
communication skillscollaborationleadership
Certifications
Master's degreePhD