Applied Scientist, Amazon Compliance and Safety Services
at Amazon
Posted 5 hours ago
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Amazon's Compliance and Safety Services (CoSS) Team seeks an Applied Scientist to advance NLP, multi-modal modeling, domain adaptation, continual learning, and large language model research for product compliance and safety. You will work with tabular, textual, and image data across product pages, seller details, and customer feedback to develop algorithms that improve safety and customer trust, and collaborate with engineers, PMs, and product managers to deploy ML solutions across the catalog. The role involves designing new algorithms, planning data labeling and audit mechanisms, evaluating results, publishing research, and contributing to roadmaps. The team focuses on image and document understanding to support compliance and anomaly detection.
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.
Key job responsibilities
As an Applied Scientist on our team, you will:
- 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.
About the team
The science team delivers custom state-of-the-art algorithms for image and document understanding. The team specializes in developing machine learning solutions to advance compliance capabilities. Their research contributions span multiple domains including multi-modal modeling, unstructured data matching, text extraction from visual documents, and anomaly detection, with findings regularly published in academic venues.
Basic Qualifications
- PhD, or a Master's degree and experience in CS, CE, ML or related field- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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
- 5+ years with neural deep learning methods and machine learning
Preferred Qualifications
- Experience using Unix/Linux- Experience in professional software development
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