Applied Scientist Ii, Alexa Artificial Intelligence
6 days ago
Master’s in computer science, statistics or a related field
2-7 years experience in machine learning and data science
Experience in Python, or another language; command line usage; familiarity with Linux and AWS ecosystem
Expertise in machine learning and in particular deep neural networks
Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.
Job summary
We’re looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading technologies that push forward the frontiers of conversational AI. Our team’s mission is to work with both internal and external teams to advance the state-of-the-art in conversational AI.
Key job responsibilities
As an Applied Scientist with the Alexa Artificial Intelligence (AI) team, you will be responsible for developing novel algorithms that advance the state-of-the-art in areas such as natural understanding, dialog management, natural language generation, multimodal interaction, and knowledge acquisition. You will work with partner science and engineering teams across Alexa AI and Amazon more broadly to create machine learning architectures and frameworks that facilitate engagement of external teams on key research challenges for the field, through competitions such as the Alexa Prize challenges. You will help to define new challenges and develop novel approaches for evaluation and analytics on challenge data.
A day in the life
You will work in a hybrid and fast-paced organization where scientists and engineers work together to drive new technologies to production. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon.
About the team
Master’s or PhD in computer science, statistics or a related field
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
Papers published in AI/ML venues of repute
The motivation to achieve results in a fast-paced environment.
Exceptional level of organization and strong attention to detail
Comfortable working in a fast paced, highly collaborative, dynamic work environment
Ability to think creatively and solve problems
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