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As an Applied Scientist in the Alexa AI team, you will spearhead the advancement and deployment of state-of-the-art ML/RAG systems that revolutionize how millions of customers interact with Alexa. You'll leverage your expertise in machine learning, natural language processing, and large language models to create reliable, scalable, high-performance products that set new standards in operational excellence. Working at the intersection of research and production, you'll translate latest AI innovations into customer-facing features that delight users daily. Your work will span the full ML lifecycle—from analyzing customer behavior patterns and building novel metrics for personal digital assistants, to deploying automated training pipelines and conducting rigorous A/B testing across diverse devices and endpoints. Collaborating closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver measurable customer impact. This role offers the unique opportunity to publish at top-tier conferences while seeing your innovations scale to one of the world's most popular voice assistants, serving millions of customers globally.
Job Responsibility
Analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints
Create deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences
Build and deploy automated model training and evaluation pipelines
Implement complex machine learning and deep learning algorithms
Conduct rigorous model and data analysis through online A/B testing
Research and implement novel approaches that push the boundaries of what's possible in conversational AI
Ensure operational excellence by taking ownership of production systems, including on-call responsibilities
Deploy fixes and handle high-severity issues alongside Software Development Engineers
Requirements
PhD, or a Master's degree and experience in Computer Science, Computer Engineering, Machine Learning or related field
Experience building machine learning models or developing algorithms for business application
Strong proficiency in programming languages such as Python or Java, with deep expertise in machine learning frameworks
Experience in any of the following areas: algorithms and data structures, algorithms, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team setting.
Nice to have
Several years of building machine learning models or developing algorithms for business application experience
Have publications at top-tier peer-reviewed conferences or journals
Track record of diving into data to discover hidden patterns and conducting error/deviation analysis
Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
Exceptional level of organization and strong attention to detail