About the job
The AWS Data Center Engineering - BIM & AI Technologies team is seeking a Principal Applied Scientist to lead the science vision for AI-powered design automation across Amazon's global data center infrastructure. Our team builds state-of-the-art machine learning systems that automate building design tasks in BIM environments, ensure compliance with building codes and design standards, and accelerate facility design workflows at an unprecedented scale.
Responsibilities
Define and drive the science roadmap for AI-powered BIM design automation, balancing foundational research with incremental product improvements aligned to business priorities
Lead the design, development, and deployment of production-grade ML models for BIM and AECO applications, including fine-tuning foundation models on domain-specific datasets and optimizing performance through iterative experimentation
Research innovative machine learning approaches and identify new opportunities for GenAI applications in the building engineering and design domain across both structured and unstructured data
Drive end-to-end GenAI projects with high complexity and ambiguity from conception to production, spanning foundation models, graph neural networks, NLP, reinforcement learning, and computer vision applied to real-world engineering challenges at scale
Build scalable ML infrastructure and pipelines for training, fine-tuning, and deploying models on large-scale BIM datasets representing digital twins of physical facilities
Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional teams to ensure robust deployment with human-in-the-loop controls
Publish research findings at top-tier ML conferences and journals, and represent the team in the broader science community through tech talks and publications
Mentor scientists and engineers at all levels, establish ML best practices, and drive technical excellence across the organization
Engage with cross-functional stakeholders, including senior leadership, to drive alignment, influence product roadmaps, and communicate technical strategy
Qualifications
Minimum
8+ years of building machine learning models or developing algorithms for business application experience
PhD, or Master's degree and 10+ years of experience in CS, CE, ML, or a related field
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience in several of the following areas: generative AI, deep learning, computer vision, graph neural networks, reinforcement learning, natural language processing, multimodal learning, or information retrieval
Preferred
deep theoretical foundations in machine learning; practical experience applying ML to domain-specific problems; understanding of Architecture, Engineering, Construction, and Ownership (AECO) professionals' high trust bars; ability to solve hard problems where advanced research meets real-world engineering challenges