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Applied Scientist II, Alexa Ads

Bengaluru, Karnataka, India💼 Full-time🗓 2026-06-17 → 2026-07-31

Core

Building machine learning models for natural language processing, recommendation systems, and personalization to integrate advertising into the Alexa experience.

Role type

Applied Scientist (NLP/Recommendation Systems)

Builds

Agentic Advertising products and personalized user interactions for Alexa

Domain

Consumer AI, Computational Advertising, Voice-First Interfaces

Deliverable

production ML models

Required skills

NLP, recommendation systems, deep learning, A/B experimentation, scalable ML pipelines, Java, C++, Python, algorithms and data structures, numerical optimization, data mining, parallel and distributed computing

Preferred skills

Unix/Linux, professional software development

Technologies

Java, C++, Python

Responsibilities

Design and develop innovative ML and deep learning models for NLP and recommendation systems; conduct hands-on data analysis and build scalable ML pipelines; design and run A/B experiments to measure model impact; collaborate with engineers to deploy models into high-scale, real-time production environments.

Seniority

Mid-Senior, hands-on IC

Rewrite
## 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. ## Requirements - 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 ## Nice to Have - Experience using Unix/Linux - Experience in professional software development ## Benefits 🧪 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.
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