Applied Scientist II, Alexa Ads

Alexa is the worlds best Generative AI powered personal assistant / agent for consumers. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Conversational Ads and this role you will build machine learning models that seamlessly and naturally integrate relevant advertising into the Alexa experience while deeply personalizing user interactions. You will work closely with other scientists engineers and product managers to take models from conception to production.

Key job responsibilities
Design develop and evaluate innovative deep learning and GenAI models for natural language processing (NLP) recommendation systems and personalization.
Conduct hands-on data analysis and build scalable ML pipelines.
Design and run A/B experiments to measure the impact of new models on customer experience and ad performance.
Collaborate with software development engineers to deploy models into high-scale real-time production environments.

About the team
We are building a new science team in Bangalore to solve some of the most impactful problems in computational advertising. This isnt about tweaking existing models as we are rethinking how ads are ranked priced and personalized across voice-first and screen-first surfaces. These are problems that dont have textbook solutions. Key points to note about the team:

Greenfield team - you are not joining a mature org with rigid processes. You will shape the science roadmap pick the problems and define the culture from day one.

Direct business impact your models directly drive revenue. No yearly cycles to see if your work matters.

Global scope local autonomy collaborate with scientists and engineers across Seattle Sunnyvale and Bangalore but own your problem space end-to-end.

Ship AND Publish: We encourage top-tier publications (NeurIPS ACL EMNLP KDD ICML WWW) while ensuring your research hits production.

- 4 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Experience using Unix/Linux
- Experience in professional software development
- 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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