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Sr. Applied Scientist, Alexa International
Amazon
On-siteseniorPosted June 3, 2026
About the Role
Develop novel algorithms and modeling techniques for multilingual speech generation and synthesis, leveraging deep learning and Generative AI to enhance Alexa's voice experiences in international markets.
Requirements
Seeks a Senior Applied Scientist with expertise in speech models, deep learning, and Generative AI to develop novel algorithms for multilingual speech generation, text-to-speech synthesis, and speech-to-speech models for Alexa.
Full Job Description
The Alexa International Science team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong background in speech models (understanding and generation) and deep learning, to help build industry-leading Generative AI technology with speech-to-speech models and multilingual systems. At this level, you will drive cross-team scientific strategy for speech quality across international locales, influence partner teams, and deliver solutions that have broad impact across Alexa's global products.
Key job 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 in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality.
A day in the life
You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale.
About the team
The Alexa International Tech team helps Alexa+ global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms.
Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.
Key job 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 in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models. Your work will directly impact customers across multiple languages in the form of natural, expressive, and locale-appropriate voice experiences for Alexa+. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales. The ideal candidate possesses a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. They thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback, and are able to influence and align multiple teams around a shared scientific vision for international speech quality.
A day in the life
You will start your day reviewing experiment results and iterating on model architectures for speech generation. You will collaborate with software engineers to optimize model performance for production deployment, and partner with product managers to align research priorities with customer needs. You will participate in science reviews, paper reading groups, and brainstorming sessions with fellow scientists across the organization. Your work directly impacts how Alexa sounds and communicates with customers in international markets, making every day an opportunity to solve meaningful problems at global scale.
About the team
The Alexa International Tech team helps Alexa+ global expansion scalable, reliable, and locally relevant for customers. We build the science, engineering, evaluation, and quality platforms behind global AI product delivery: multi-model AI orchestration, multilingual model and data readiness, speech and language quality, reward modeling, synthetic data generation, automated evaluation, developer tooling, defect analysis, and launch mechanisms.
Our work sits at the intersection of applied AI, speech, distributed systems, developer experience, and customer quality automation. The goal is simple but hard: help teams build Alexa+ experiences once and scale them across languages, countries, devices, models, and customer expectations without reinventing the same mechanisms every time.