Applied Scientist II, Alexa Ads

Amazon; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Amazon India is seeking an Applied Scientist to join the Alexa Agentic/Conversational Ads and Personalization team in Bengaluru. You will build ML models to integrate advertising into Alexa experiences with deep personalization and collaborate with cross-functional teams to take models from conception to production.

The role focuses on NLP, recommendation systems, and real-time deployment at scale, with opportunities for publication and direct business impact on revenue.

Qualifications

• 3+ years building models for business applications.
• PhD or Master's + 4+ years CS/ML or related field experience.
• Experience with patents or publications at top-tier venues.
• Proficiency in Java, C++, Python.
• Strong foundations in algorithms, data structures, optimization.

Responsibilities

• Design, develop, and evaluate ML/NLP models for personalization and ads.
• Build scalable ML pipelines and conduct hands-on data analysis.
• Design and run A/B experiments to measure impact on experience and ad performance.
• Collaborate with engineers to deploy models in production environments.

Skills

NLP models

ML pipelines

A/B testing

Java/Python/C++

Publication experience

Education

PhD or MS + 4+ years

Tools

Java

Python

C++

Unix/Linux

Job description

Description

Alexa+ is the world’s best Generative AI powered personal assistant / agent for consumers, and is becoming the conversational AI interface for Amazon services with the launch of Alexa for Shopping on Amazon.com and Amazon mobile app. At Alexa Ads, we are creating industry's first and most advanced Agentic Advertising products to drive Agentic Commerce. We are seeking an Applied Scientist to join our newly expanding team in India focused on Alexa Agentic/Conversational Ads and Personalization. In 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 machine learning and deep learning 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 isn't 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 don't 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.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's 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

Preferred Qualifications

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

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