Applied Scientist, Alexa Sensitive Content Intelligence (ASCI)

Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly.

The Mission
Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale.

What You'll Build
You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations.

Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI.

This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions.

What We're Looking For

* Deep expertise in state-of-the-art NLP, Large Language Models
* Track record of building scalable ML systems
* Passion for impactful research—where frontier science meets real-world responsibility at scale
* Excitement about solving problems that will shape the future of AI

Ready to work on AI safety challenges that define the industry? Join us.

Key job responsibilities
The Responsible AI (RAI) team is at the forefront of building AI systems that are safe, ethical, and trustworthy. As an Applied Scientist-II, you'll be a key contributor to end-to-end Responsible AI solutions—developing and refining algorithms that detect and eliminate false information, building models that identify vulnerabilities exploited by bad actors, and training systems that understand human values across diverse cultures. Working alongside world-class engineers and scientists, you'll apply state-of-the-art NLP and computer vision techniques to content classification and safety challenges—turning cutting-edge research into production systems that protect millions of customers daily.

But here's what makes this role exciting: you'll grow into a future leader. You'll contribute to identifying, defining, and mitigating AI safety risks early—helping protect customers before they're impacted—while building deep expertise in responsible AI. You'll work within multi-agent architectures, implementing components where distributed AI systems maintain human oversight and control. Every model you build and every experiment you run—from consensus-driven reasoning modules to orchestration components—will directly strengthen trustworthy AI at the world's largest scale.
But here's what makes this role truly special: you'll shape the future. You'll lead efforts to identify, define, and mitigate risks early—protecting customers before they're impacted—and mentor the next generation of AI safety experts. You'll design multi-agent architectures where distributed AI systems exhibit emergent collective intelligence while maintaining human oversight and control. Every innovation you drive—from consensus-driven reasoning frameworks to sophisticated orchestration patterns—will set new standards for trustworthy AI at the world's largest scale.

A day in the life
As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values.

About the team
Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.

Basic qualifications

- Experience building machine learning models or developing algorithms for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Preferred qualifications

- Experience using Unix/Linux
- Experience with programming languages such as Python, Java, C++

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