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, NLP, and LLMs to create reliable, scalable, high-performance products that raise the bar in operational excellence. Working closely with business, engineering, and science teams across Amazon, you'll lead high-visibility programs that automate workflows and deliver customer-impacting results through innovative AI solutions.

Key job responsibilities

As an Applied Scientist in the Alexa AI team:

• You'll analyze and model customer behavior at scale, building novel metrics for personal digital assistants across diverse devices and endpoints. Your work will involve creating deep learning, policy-based learning, and machine learning algorithms that directly impact customer experiences, translating complex data patterns into actionable insights that drive product innovation.

• Your technical leadership will extend to building and deploying automated model training and evaluation pipelines, implementing complex machine learning and deep learning algorithms, and conducting rigorous model and data analysis through online A/B testing. You'll research and implement novel approaches that push the boundaries of what's possible in conversational AI.

• Beyond model development, you'll ensure operational excellence by taking ownership of production systems, including on-call responsibilities during peak and non-peak hours. Working alongside Software Development Engineers, you'll deploy fixes and handle high-severity issues, ensuring our ML systems maintain the reliability and performance that millions of Alexa customers depend on daily.

A day in the life
As an Applied Scientist in the Alexa AI team, your day will involve collaborating with talented engineers and scientists to build scalable solutions for our conversational assistant. You'll dive into data analysis, experiment with novel algorithms, and iterate on models based on real-time user feedback. Working in a fast-paced, ambiguous environment, you'll tackle complex technical challenges—from debugging production issues to presenting research findings to stakeholders. Your self-motivated approach will drive you to swiftly deliver impactful solutions while maintaining the high standards that define our mission to revolutionize user experiences for millions of customers.

About the team
The Alexa AI team develops the intelligence behind one of the world's most popular voice assistants, serving millions of customers globally. We're a diverse group of scientists, engineers, and researchers united by our mission to make Alexa more natural, helpful, and delightful. Our culture thrives on innovation, collaboration, and customer obsession. We tackle some of the most challenging problems in conversational AI—from natural language understanding to personalization at scale. Here, you'll work alongside world-class talent, publish at top-tier conferences, and see your innovations impact customers daily. We move fast, think big, and celebrate both successes and learnings.

Basic Qualifications

• 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
• Bar raising knowledge of programming languages such as Python or Java, with a strong focus on 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.

Preferred Qualifications

• 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
• Fluent in written and spoken English

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