Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
The Alexa International Science team is seeking a passionate, talented, and inventive Applied Science Manager with a strong background in speech models (understanding and generation) and deep learning. You will lead a team building industry-leading Generative AI technology focused on speech-to-speech models and multilingual systems. This role involves driving cross-team scientific strategy for speech quality across international locales, influencing partner teams, and delivering solutions with broad impact across Alexa's global products.

You will own programs with global visibility and collaborate with a cross-functional group of Science, Product, and Engineering leaders. Your team's 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+. Leveraging Amazon's heterogeneous data sources and large-scale computing resources, you will accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales.

The ideal candidate has a solid understanding of machine learning, speech synthesis (TTS/S2S), multilingual phonetics, modern model architectures, and evaluation methodology. You thrive in a fast-paced environment, tackle complex challenges in low-resource language settings, and can 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 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 Amazon's LLMs with human preferences
- Identify and prioritize research opportunities with significant impact potential
- Mentor and guide team members to achieve career goals
- Communicate research findings and progress to senior leadership and stakeholders
- Rapidly experiment and drive productization to deliver customer impact
- Drive academic partnership with top-tier Indian university as part of the org's AI/ML Center initiative
- Participate in and drive science publications in peer-reviewed venues

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. The team works at the intersection of speech science, LLMs, and international product launches.

Experience
- Direct experience managing scientists or machine learning engineers
- Experience building complex, highly-scalable systems involving predictive models or machine learning applications

About You
- Strong background in machine learning, speech synthesis (TTS/S2S), multilingual phonetics, and modern model architectures
- Ability to thrive in a fast-paced environment and tackle complex challenges, especially in low-resource language settings
- Skilled at influencing and aligning multiple teams around a shared scientific vision
- Excellent communication skills to convey research findings to senior leadership and stakeholders

Qualifications
- Master's degree or PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field
- Knowledge of ML, NLP, Information Retrieval, and Analytics
- Preferred: Experience building machine learning models or algorithms for business applications
- Preferred: Experience delivering complex software systems involving deep learning, machine learning, or computer vision to customers