Senior Applied Scientist, Alexa Enterprise Products (AEP)

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 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.

AE team is looking for a passionate, highly skilled and inventive Senior 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 a Senior 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
- You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence
- You will 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- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- Solid Machine Learning background and familiar with SOTA machine learning techniques

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.