Senior Applied Scientist, Alexa Ads

Amazon; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Amazon in Bengaluru is seeking an Applied Scientist to advance Alexa Agentic/Conversational Ads and Personalization. You will build ML models that integrate advertising into the Alexa experience while personalizing user interactions, collaborating with scientists, engineers and PMs to take models from concept to production.

You will work on deep learning for NLP, recommendation systems, and personalization, and you will have opportunities to publish in top conferences while shipping impactful

Qualifications

• 6+ years building ML models for business applications.
• PhD or Master’s with 6+ years of applied research.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and ML.

Responsibilities

• Design, develop, and evaluate deep learning and GenAI models for NLP, recommendations, and personalization.
• Conduct hands-on data analysis and build scalable ML pipelines.
• Design and run A/B experiments to measure model impact on user experience and ad performance.
• Collaborate with engineers to deploy models into large-scale real-time production.

Skills

Machine learning

NLP

Deep learning

Programming (Java, C++, Python)

Education

PhD or Master’s + 6+ years

Tools

TensorFlow

scikit-learn

Spark MLLib

MxNet

Hadoop

Spark

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 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

• ? 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

• 6+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

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