About the job
The Alexa AI Domains is seeking a passionate, talented, and resourceful Senior Applied Scientist to invent and build scalable solutions for sate-of-the-art conversational AI. You will be working on advancing technologies in the fields of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval. As part of this role, you will collaborate with talented peers, have significant influence on our overall strategy as you guide and mentor Applied Scientists to create innovative and scalable solutions that touch millions of Alexa customers.
Responsibilities
Define the science roadmap and advance core science primitives for conversation modelling, content generation, and automated quality assurance via state-of-the-art computer vision, machine learning, and generative AI
Architect agentic systems, making high-judgment trade-offs across audio/text/visual quality, relevance, latency, cost, and long-term extensibility
Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, institutionalizing rigorous validation across customer touch points
Own end-to-end delivery of complex, ambiguous research initiatives from problem formulation through experimentation to production deployment, with minimal guidance
Identify whitespace opportunities by staying at the forefront of AI/ML advances and translating them into actionable research directions with clear customer and business impact
Drive development and deployment of scalable agentic systems for conversation understanding and generation, ensuring architectural decisions support long-term platform evolution
Set and continuously raise the scientific and engineering bar across the team
Tackle the team's most complex technical problems while maintaining practical focus on customer value and solution generalizability
Advance the team's scientific reputation through high-impact publications and presentations at top-tier internal and external venues, and generate intellectual property through patents
Qualifications
Minimum
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
Preferred
Experience in building machine learning models for business application
Experience with large scale distributed systems such as Hadoop, Spark etc.
Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
Usage of Generative AI tools to enhance workflow efficiency, with a willingness to learn effective agentic prompting and evaluation practices