Applied Scientist, AWS Applied AI Solutions Core Services

Amazon • Seattle, WA

1d

About The Position

As part of the AWS Applied AI Solutions organization, we're building the future
of AI-powered enterprise services across multiple domains. Our vision is to be
the trusted foundation for transforming every business with Amazon AI teammates.
Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities
that create delightful AI powered solutions. We're developing sophisticated AI
systems that address complex challenges across autonomous operations, geospatial
intelligence, trust and safety, IoT services, and foundational AI platforms.

As an Applied Scientist, you'll work on challenging problems that span multiple
domains within AWS Core Services. You might develop video processing
architectures for autonomous systems, create optimization solvers for geospatial
applications, build behavioral detection models for fraud prevention, design
anomaly detection systems for IoT devices, or develop specialized AI
capabilities for platform services. You'll investigate novel approaches,
validate ideas through rigorous experimentation with real data, and collaborate
with scientists and engineers to transform research insights into scalable
solutions.

Our team is a central science organization supporting multiple product teams
across AWS Core Services. We tackle fundamental challenges in AI and machine
learning that require novel approaches beyond off-the-shelf solutions. Working
at the intersection of machine learning, large language models, and
domain-specific applications, we develop practical techniques that advance the
state-of-the-art while maintaining a clear path to customer impact. Our team
builds deep domain expertise across geospatial intelligence, trust and safety
systems, autonomous operations, and other critical areas, collaborating closely
with engineering teams to transform research insights into scalable production
solutions.

Requirements

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice To Haves

• Experience using Unix/Linux
• Experience in professional software development

Responsibilities

• Develop and productize AI solutions that address complex technical challenges requiring novel approaches beyond off-the-shelf tools
• Design and implement machine learning systems for diverse applications including video understanding, geospatial optimization, fraud detection, anomaly detection, and automation
• Create scalable algorithms and models that generalize across multiple customer use cases and business problems
• Conduct rigorous experimentation with state-of-the-art techniques including large language models, computer vision, federated learning, or physics-based modeling, and agentic AI systems
• Collaborate with engineering teams to integrate science components into production systems with measurable customer impact
• Work directly with product teams to understand requirements, frame ambiguous problems into tractable science solutions, and validate approaches through proof of concepts
• Establish evaluation frameworks and best practices for measuring solution performance and business impact
• Mentor other scientists and contribute to the broader scientific community through publications when appropriate

Benefits

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree