Amazon Data Services, Inc.
Technology
PrincipalAppliedScientist,DataCenterDesignEngineering-BIM&AITechnologies
Neural analysis suggests this role is
optimal for Principal candidates.
“Principal Applied Scientist, Data Center Design Engineering - BIM & AI Technologies at Amazon Data Services, Inc.. Skills: Machine Learning, Generative AI, Graph Neural Networks, Natural Language Processing. Define science roadmap for AI-powered BIM design automation. Lead design, development, deployment of ML models”
What You'll Achieve.
Measurable customer impact
Industry & Context.
Solving hard problems
What They're Looking For.
Must Have
8+ years building ML models, PhD or Master's degree, 10+ years experience in CS, CE, ML, Experience in patents or publications, Experience programming in Java, C++, Python, Experience in generative AI, Experience in deep learning, Experience in computer vision, Experience in graph neural networks, Experience in reinforcement learning, Experience in natural language processing, Experience in multimodal learning, Experience in information retrieval
Nice to Have
Creating novel algorithms, Advancing the state of the art, Leading experienced scientists, Developing junior members, First author publications at Tier-1 ML conferences, Bridging research with practical engineering, Building and scaling agentic AI applications, Experience with AEC industry data, Experience with BIM data, Experience with CAD data, Experience with 3D geometry data, Experience with spatial computing data, Experience with construction drawings data, Experience with specifications data, Experience with building code regulations data
What You'll Do.
Define science roadmap for AI-powered BIM design automation
deployment of ML models
Fine-tune foundation models on domain-specific datasets
Optimize performance through iterative experimentation
Research innovative machine learning approaches
Identify new opportunities for GenAI applications
Drive end-to-end GenAI projects
Build scalable ML infrastructure and pipelines
deploy models on BIM datasets
Translate research advances into customer-facing products
Ensure robust deployment with human-in-the-loop controls
Publish research findings at top-tier ML conferences
Represent team in science community
Mentor scientists and engineers
Establish ML best practices
Drive technical excellence
Engage with cross-functional stakeholders
Influence product roadmaps
Communicate technical strategy
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering teams; Product teams; Senior leadership
Communication Scope
Tech talks; Publications
Full Job Description
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. 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. In this role, you will define and drive 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). You will own end-to-end technical solutions from research through production deployment, working alongside architects, structural engineers, MEP engineers, construction managers, software engine
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