Senior Applied Scientist, Alexa International

Amazon
USA, WA, Bellevue2026-05-13ONSITE

About the job

Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge. At this level, you will drive cross-team scientific strategy, influence partner teams, and deliver solutions that have broad impact across Alexa's international products and services.

Responsibilities

As a Senior Applied Scientist with the Alexa International team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs, particularly delivering industry-leading scientific research and applied AI for multi-lingual applications — a challenging area for the industry globally. Your work will directly impact our global customers in the form of products and services that support Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in text, speech, and vision domains. The ideal candidate possesses a solid understanding of machine learning, speech and/or natural language processing, modern LLM architectures, LLM evaluation & tooling, and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fast-paced environment, like to tackle complex challenges, excel at swiftly delivering impactful solutions while iterating based on user feedback, and are able to influence and align multiple teams around a shared scientific vision.

Qualifications

Minimum

PhD, or Master's degree

4+ years of applied research experience

Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production

PhD in CS, CE, ML, or related field with 4+ years of relevant post-PhD research experience; or Master's degree with 7+ years of equivalent experience

Deep expertise in state-of-the-art LLM architectures, training, evaluation, and post-training techniques (SFT, DPO, RLHF, RLAIF)

Preferred

Experience in building speech recognition, machine translation and natural language processing systems

Experience in patents or publications at top-tier peer-reviewed conferences or journals