Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers. We are seeking an experienced Applied Science Manager to build and lead a new team of scientists in India dedicated to Alexa Conversational Ads and Personalization. As the leader of this team, you will shape both the scientific roadmap and the product strategy, working closely with global product stakeholders to ensure your team is delivering high-impact, scalable solutions.

Key job responsibilities
- Hire, develop, and mentor a high-performing team of applied scientists.

- Partner with product management and engineering leadership to define the mid-to-long-term scientific roadmap for conversational ads and personalization.

- Manage the execution of complex ML projects, ensuring rigorous experimental design, high modeling standards, and on-time delivery.

- Bridge the gap between science, engineering, and product, translating business metrics into scientific goals and vice versa.

- Establish best practices for ML lifecycle management, code quality, and technical documentation within the team.

Basic Qualifications

- Master's degree or above in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- 6+ years of building machine learning models for business application experience
- 3+ years of direct people leadership experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience debugging, profiling, and implementing best software engineering practices in large-scale systems
- Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders

Preferred Qualifications

- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience (technical and operational) with multiple domain areas of programmatic advertising technologies (DSP, RTB, bid shading, machine learning optimization, ad verification, ad tracking, ad attribution, etc.)
- Experience building large-scale machine learning models and infrastructure for online recommendation, ads ranking, personalization, or search

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