Principal Applied Scientist, Data Center Design Engineering - BIM & AI Technologies

Amazon•Seattle, WA

1d•$198,900 - $269,000•Onsite

About The Position

AWS Infrastructure Services is responsible for the design, planning, delivery, and operation of all AWS global infrastructure, ensuring the cloud runs smoothly. This includes supporting AWS data centers and all associated equipment like servers, storage, networking, power, and cooling. The team tackles challenging problems with numerous variables impacting the supply chain, seeking talented individuals to join a diverse team of engineers, specialists, and managers. Collaboration across AWS is key to delivering high standards for safety and security, providing infinite capacity at the lowest cost, and fostering an inclusive culture that encourages bold ideas. The AWS Data Center Engineering - BIM & AI Technologies team is specifically looking for a Principal Applied Scientist to lead the science vision for AI-powered design automation across Amazon's global data center infrastructure. This team develops state-of-the-art machine learning systems to automate building design tasks in BIM environments, ensure compliance with building codes and design standards, and accelerate facility design workflows at an unprecedented scale. The role involves defining and driving the research roadmap at the intersection of generative AI, graph neural networks, natural language processing, reinforcement learning, and computer vision, applied to both structured data (BIM models, 3D geometries, spatial relationships) and unstructured data (construction drawings, specifications, regulatory documents). The Principal Applied Scientist will own end-to-end technical solutions from research to production deployment, collaborating with various engineering, design, and product teams to translate research into deployed systems with measurable customer impact. The ideal candidate possesses deep theoretical ML foundations and practical application experience, understanding the high trust requirements of Architecture, Engineering, Construction, and Ownership (AECO) professionals for AI systems that augment, rather than replace, human judgment. The role is suited for someone who thrives on solving complex problems where advanced research meets real-world engineering challenges.

Requirements

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

Nice To Haves

Experience creating novel algorithms and advancing the state of the art
Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
First author publications at Tier-1 ML conferences
Experience bridging research with practical engineering implementation
Demonstrated leadership in building and scaling agentic AI applications in production
Experience working with data from the Architecture, Engineering, Construction (AEC) industry or related domains, such as Building Information Models (BIM), CAD, 3D geometry, spatial computing, construction drawings, specifications, or building code regulations

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

Benefits

sign-on payments
restricted stock units (RSUs)
health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
paid time off
parental leave
Work-life harmony
flexibility as part of our working culture
Inclusive Team Culture
employee-led affinity groups
Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences
Mentorship and Career Growth
endless knowledge-sharing
career-advancing resources