Applied Scientist - Machine Learning and Personalization

Amazon India Limited; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Amazon India Limited is hiring an Applied Scientist II for Alexa Ads in Bengaluru. You will design and implement ML/NLP models that enhance Alexa Agentic/Conversational Ads and personalization, driving better user experiences and ad performance.

Collaborate across teams to move models from concept to production, with opportunities for impactful research publications. The role emphasizes hands-on data analysis, scalable ML pipelines, and close work with engineers and product managers to improve

Qualifications

• 3+ years building ML models for business applications.
• PhD or Master’s in CS/CE/ML or related field plus 4+ years experience.
• Experience with publications or patents at top conferences or journals.

Responsibilities

• Design, develop and evaluate ML/NLP models for NLP, recsys, and personalization.
• Conduct data analysis and build scalable ML pipelines.
• Design and run A/B experiments to measure impact on user and ad performance.
• Collaborate with software engineers to deploy models in production at scale.

Skills

ML modeling

NLP

Python

Java

C++

Distributed computing

Data mining

Education

PhD or Master in CS/CE/ML

Tools

Unix/Linux

Job description

Applied Scientist II, Alexa Ads

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.
• 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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Experience Level Mid Level