Applied Science Manager, Alexa International

The Alexa International Science team is looking for a passionate talented and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning to lead a team building industry-leading Generative AI technology with speech-to-speech models and multilingual systems.

You will lead a team of Applied Scientists drive cross-team scientific strategy for speech quality across international locales influence partner teams and deliver solutions with broad impact across Alexas global products. You will own programs with global visibility and interact with a cross-functional group of Science Product and Engineering leaders.

Your teams work will advance the state of the art in multilingual speech generation text-to-speech synthesis and speech-to-speech models directly impacting customers across 20 languages with natural expressive and locale-appropriate voice experiences for Alexa. You will leverage Amazons 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 and are able to influence and align multiple teams around a shared scientific vision.

Core Leadership and Team Management
- Lead and manage applied scientists focused on multilingual speech generation and voice personality
- Build and develop high-performing science teams focused on speech synthesis pronunciation evaluation and multilingual model adaptation
- Set technical direction and raise the bar on scientific rigor experimental methodology and publication quality
- Hire mentor and grow scientists at multiple levels

Cross-Organizational Collaboration
- Partner with cross org stakeholders to align goals and accelerate delivery
- Establish clear communication channels and workflows across organizational boundaries
- Drive alignment between science roadmaps and product launch timelines across 20 locales

Delivery and Execution
- Own end-to-end delivery of speech quality improvements from research through production deployment
- Define success metrics and evaluation frameworks for multilingual speech quality
- Balance long-term research investments with near-term launch commitments

Key job responsibilities
* Lead and manage a team of Applied and Data scientists responsible for building and enhancing capabilities for Alexa
* Collaborate with cross-functional teams to build methods to align Amazons LLMs with human preferences.
* Identify and prioritize research opportunities that have the potential to significantly impact our AI systems.
* Mentor and guide team members to achieve their career goals and objectives.
* Communicate research findings and progress to senior leadership and stakeholders.
* Rapidly experiment and drive productisation to deliver customer impact.
* Drive academic partnership with top tier Indian university as part of the orgs AI/ML Center initiative.
* Participate in and drive science publications in peer-reviewed venues of repute.

About the team
The Alexa International Science team drives multilingual AI quality for Alexa ensuring customers across all supported languages receive a natural accurate and culturally appropriate voice experience. We work at the intersection of speech science LLMs and international product launches.

- Experience directly managing scientists or machine learning engineers
- Masters degree in engineering technology computer science machine learning robotics operations research statistics mathematics or equivalent quantitative field or PhD
- Knowledge of ML NLP Information Retrieval and Analytics
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning

- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems especially involving deep learning machine learning and computer vision that have been successfully delivered to customers

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