Applied Scientist, Alexa AI

Job :  | Amazon Development Centre Italy SRL
As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state‑of‑the‑art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You’ll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high‑performance products that set new standards in operational excellence.
Working at the intersection of research and production, you’ll translate the latest AI innovations into customer‑facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints.
Collaborating closely with business, engineering, and science teams across Amazon, you’ll lead high‑visibility programs that automate workflows and deliver measurable customer impact.

This role offers the unique opportunity to publish at top‑tier conferences while seeing your innovations scale to one of the world’s most popular voice assistants, serving millions of customers globally.
Key job responsibilities

Analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Create deep learning, policy‑based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation.
Build and deploy automated model training and evaluation pipelines, implement complex machine learning and deep learning algorithms, and conduct rigorous model and data analysis through online A/B testing. Research and implement novel approaches that push the boundaries of what’s possible in conversational AI.
Ensure operational excellence by taking ownership of production systems, including on‑call responsibilities during peak and non‑peak hours. Work alongside Software Development Engineers to deploy fixes and handle high‑severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily.

A day in the life
As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You’ll dive into data analysis, experiment with novel algorithms, and iterate on models based on real‑time user feedback. Working in a fast‑paced, ambiguous environment, you’ll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders.

Your self‑motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers.
About the team
The Alexa AI team develops the intelligence behind one of the world’s most popular voice assistants, serving millions of customers globally. We’re a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization e, you’ll work alongside world‑class talent, publish at top‑tier conferences, and see your innovations impact customers daily.

We move fast, think big, and celebrate both successes and learnings.
Basic Qualifications

PhD, or a Master’s degree and experience in Computer Science, Computer Engineering, Machine Learning or related field
Experience building machine learning models or developing algorithms for business application
Strong proficiency in programming languages such as Python or Java, with deep expertise in machine learning frameworks
Experience in any of the following areas: algorithms and data structures, algorithms, parsing, numerical optimization, data mining, parallel and…