Principal Applied Scientist, Kiro Science

AWS Agentic AI is looking for a Principal Applied Scientist who will partner with world‑class scientists and engineers to pioneer the next generation of AI‑driven development tools. Join the Amazon Kiro LLM‑Training team and help create groundbreaking generative AI technologies, including Kiro IDE and Amazon Q Developer that are transforming the software development landscape.

Key Responsibilities

• Push the boundaries of reinforcement learning and post‑training methodologies for large language models specialized in code intelligence

• Invent and implement state‑of‑the‑art machine learning solutions that operate at unprecedented Amazon scale

• Deploy revolutionary products that directly impact the daily workflows of millions of developers worldwide

• Break new ground in AI and machine learning, challenging what's possible in intelligent code assistance

• Publish and present pioneering work at premier ML and NLP conferences (NeurIPS, ICML, ICLR, ACL, EMNLP)

• Accelerate innovation by working directly with customers to rapidly transition research breakthroughs into production systems

About the Team

The AWS Developer Agents and Experiences (DAE) team is reimagining the builder experience through generative AI and foundation models. We’re leveraging the latest advances in AI to transform how engineers work from IDE environments to web‑based tools and services, empowering developers to tackle projects of any scale with unprecedented efficiency.

Broadly, AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS.

Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

Why AWS?

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.

Inclusive Team Culture

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 Amaze Con conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

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.

Work/Life Balance

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.

Hybrid Work

We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in‑person collaboration and time spent face‑to‑face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

Qualifications

• PhD, or Master’s degree and 10+ years of CS, CE, ML, or related field experience

• 8+ years of building models for business application 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: AI (NLP or multi‑modality models), Deep Learning, LLM model training, graph learning, software engineering

• First author publications at Tier‑1 ML…