Senior Applied Scientist, Alexa Ads
Alexa+ is the world s best Generative AI powe'red personal assistant / agent for consumers. We are looking for a Senior Applied Scientist to provide technical leadership for our Alexa Conversational Ads and Personalization initiatives. You will be responsible for tackling our most ambiguous scientific challenges, setting the technical architecture for new ML systems, and pushing the boundaries of what is possible in voice-based advertising.
Define the scientific vision and lead the technical execution for complex, multi-quarter ML projects in conversational ads and personalization.
Architect end-to-end machine learning systems that operate at Alexas massive scale.
Mentor and guide junior scientists on modeling techniques, experimental design, and best practices.
Partner closely with product and engineering stakeholders to translate ambiguous business requirements into rigorous scientific problem statements.
Contribute to the broader scientific community through internal technical papers and external publications. 6+ years of building machine learning models for business application experience
PhD, or Masters degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience debugging, profiling, and implementing best software engineering practices in large-scale systems Experience with and deep understanding of advertising technologies (ie, ad server, DSP)
Experience building large-scale machine learning models and infrastructure for online recommendation, ads ranking, personalization, or search
Define the scientific vision and lead the technical execution for complex, multi-quarter ML projects in conversational ads and personalization.
Architect end-to-end machine learning systems that operate at Alexas massive scale.
Mentor and guide junior scientists on modeling techniques, experimental design, and best practices.
Partner closely with product and engineering stakeholders to translate ambiguous business requirements into rigorous scientific problem statements.
Contribute to the broader scientific community through internal technical papers and external publications. 6+ years of building machine learning models for business application experience
PhD, or Masters degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience debugging, profiling, and implementing best software engineering practices in large-scale systems Experience with and deep understanding of advertising technologies (ie, ad server, DSP)
Experience building large-scale machine learning models and infrastructure for online recommendation, ads ranking, personalization, or search
