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Job Details
Posted date: Apr 20, 2026
There have been 870 jobs posted with the title of Principal Applied Scientist all time at Amazon.There have been 870 Principal Applied Scientist jobs posted in the last month.
Location: Seattle, WA
Estimated salary: $233,950
Range: $198,900 - $269,000
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 engineers, UX designers, and product managers to translate research breakthroughs into deployed systems with measurable customer impact.
The ideal candidate combines deep theoretical foundations in machine learning with practical experience applying ML to domain-specific problems. You understand that Architecture, Engineering, Construction, and Ownership (AECO) professionals maintain exceptionally high trust bars and require AI systems that augment rather than replace professional judgment. You thrive on solving hard problems where advanced research meets real-world engineering challenges.
Key job 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
About the team
Why AWS
o Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences
o Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work/Life Balance
o We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
o Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
o We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Qualifications
- 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
Extended Qualifications
- 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
- 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually