Applied Scientist, Alexa Enterprise

Alexa Enterprise Applied Scientist Opportunity

Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in the Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems.

The AE team is looking for a passionate, highly skilled and inventive Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As an Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences.

Key job responsibilities:

• Analyze, understand and improve user experiences by leveraging Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence
• Work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases
• Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints
• Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results
• Perform model/data analysis and monitor metrics through online A/B testing