As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art LLM systems that revolutionize how millions of customers interact with Alexa across many languages and locales. 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 adapting and post-training large language models (SFT, RL, DPO) and conducting rigorous A/B testing across diverse devices, endpoints, and languages.
Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact, helping bring a consistent experience to customers in every language they speak. 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
As an Applied Scientist in the Alexa AI team:
- You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices, endpoints, and languages. Your work will involve creating 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.
- Your technical leadership will extend to adapting large language models through supervised fine-tuning, reinforcement learning, and preference optimization (SFT, RL, DPO), building and deploying automated training and evaluation pipelines, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of conversational AI, including how it generalizes across multiple languages and scripts.
- Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll 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, fine-tune and align LLMs, 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 multilingual natural language understanding to personalization at scale. Here, 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.
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