Senior Applied Scientist, Alexa Ads

About the Role

Alexa+ is the leading Generative AI-enabled personal assistant, serving as the conversational AI interface for Amazon services including Alexa for Shopping on Amazon.com and the Amazon mobile app. Alexa Ads is pioneering the development of Agentic Advertising products to enable Agentic Commerce. We are expanding our team in Bengaluru, India, and seeking a Senior Applied Scientist to focus on Alexa Agentic/Conversational Ads and Personalization. The successful candidate will develop machine learning models that integrate relevant advertising naturally into the Alexa experience, enhancing user personalization. This role involves close collaboration with scientists, engineers, and product managers to deploy models from design through production.

Key Responsibilities

• Design, build, and assess innovative deep learning and Generative AI models for natural language processing, recommendation systems, and personalization.
• Perform hands-on data analysis and develop scalable machine learning pipelines.
• Plan and execute A/B testing to evaluate model impact on customer experience and advertising metrics.
• Work with software engineers to implement models in large-scale, real-time production environments.

Team Overview

• This is a greenfield team in Bangalore, focused on pioneering solutions for computational advertising rather than incremental model tweaks.
• Shape the science strategy, define key problems, and influence team culture from the start.
• Deliver direct business value as your models impact revenue without long evaluation delays.
• Engage in cross-location collaboration with Seattle, Sunnyvale, and Bangalore teams while owning your projects end-to-end.
• Balance research with production deployment, encouraged to publish in leading conferences such as NeurIPS, ACL, EMNLP, KDD, ICML, and WWW.

Required Qualifications

• At least 6 years’ experience developing machine learning models for business applications.
• PhD or Master’s degree accompanied by 6+ years of practical research.
• Proficient programming skills in Java, C++, Python, or similar languages.
• Strong background in neural deep learning techniques and machine learning methodologies.

Preferred Qualifications

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

Additional Information

Our inclusive work culture empowers all employees to achieve outstanding outcomes. Accommodations are available throughout the application and hiring process for candidates with disabilities upon request. For assistance, please contact your recruiting partner.