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Amazon's Compliance and Safety Services (CoSS) Team is looking for a smart and creative Applied Scientist to apply and extend state-of-the-art research in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model to join the Applied Science team. At Amazon, we are working to be the most customer-centric company on earth. Millions of customers trust us to ensure a safe shopping experience. This is an exciting and challenging position to drive research that will shape new ML solutions for product compliance and safety around the globe in order to achieve best-in-class, company-wide standards around product assurance. You will research on large amounts of tabular, textual, and product image data from product detail pages, selling partner details and customer feedback, evaluate state-of-the-art algorithms and frameworks, and develop new algorithms to improve safety and compliance mechanisms. You will partner with engineers, technical program managers and product managers to design new ML solutions implemented across the entire Amazon product catalog.
Job Responsibility:
Research and Evaluate state-of-the-art algorithms in NLP, multi-modal modeling, domain adaptation, continuous learning and large language model.
Design new algorithms that improve on the state-of-the-art to drive business impact, such as synthetic data generation, active learning, grounding LLMs for business use cases
Design and plan collection of new labels and audit mechanisms to develop better approaches that will further improve product assurance and customer trust.
Analyze and convey results to stakeholders and contribute to the research and product roadmap.
Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research
Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software
Publish research publications at internal and external venues.
Requirements:
PhD, or a Master's degree and experience in CS, CE, ML or related field
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience with programming languages such as Python, Java, C++
Experience in building machine learning models for business application
5+ years with neural deep learning methods and machine learning
Nice to have:
Experience in professional software development
Experience implementing algorithms using toolkits and self-developed code
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience working cross functionally across several teams
Experience with statistical modeling / machine learning