ADCI
Applied Science, alexa and amazon devices
AppliedScientistII,AlexaAds
Neural analysis suggests this role is
optimal for Mid candidates.
“Applied Scientist II, Alexa Ads at ADCI. Skills: Machine learning, Deep learning, GenAI, NLP. Design deep learning models. Develop deep learning models”
What You'll Achieve.
Drive revenue; Impact customer experience; Impact ad performance
Industry & Context.
Problems without textbook solutions
What They're Looking For.
Must Have
4+ years building models, Master's degree and 4+ years experience, Experience in patents or publications, Experience programming in Java, C++, Python, Experience in algorithms and data structures, Experience in parsing, Experience in numerical optimization, Experience in data mining, Experience in parallel and distributed computing, Experience in high-performance computing
Nice to Have
Experience using Unix/Linux, Experience in professional software development, Experience with programmatic advertising technologies, Experience building large-scale ML models
What You'll Do.
Design deep learning models
Develop deep learning models
Evaluate deep learning models
Evaluate GenAI models
Conduct data analysis
Design A/B experiments
Collaborate with engineers
How You'll Work.
Team & Collaboration
Scientists; Engineers; Product managers
Full Job 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 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
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