Applied Scientist, Artificial General Intelligence - Data Services

Requirements

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience using Unix/Linux
• Experience in professional software development
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, MA, Boston - 142,800.00 - 193,200.00 USD annually

Additional Information

AI is the most transformational technology of our time, capable of tackling some of humanity's most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for an Applied Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Applied Scientist will: - Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. - Clean, analyze and select speech/language/other data to achieve goals - Build and test models that elevate the customer experience - Collaborate with colleagues from science, engineering and business backgrounds - Present proposals and results in a clear manner backed by data and coupled with actionable conclusions - Work with engineers to develop efficient data querying infrastructure for both offline and online use cases

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