Senior Applied Research Scientist, RISC
3 days ago
We are seeking an exceptional Senior Applied Scientist to join our team of experts in the field of machine learning. As a key member of our team, you will work together to tackle challenging problems across diverse compliance domains, leveraging and training state-of-the-art multi-modal and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog.
Key Responsibilities- Design and evaluate state-of-the-art algorithms and approaches in multi-modal classification, large language models (LLMs), intent detection, information retrieval, anomaly and fraud detection, and generative AI.
- Translate product and CX requirements into measurable science problems and metrics.
- Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact.
- Key author in writing high-quality scientific papers in internal and external peer-reviewed conferences.
As a Senior Applied Scientist, you will spend your days understanding customer problems, project timelines, and team/project mechanisms. You will propose science formulations and brainstorm ideas with your team to solve business problems, write code, and run experiments with re-usable science libraries. You will review labels and audit results with investigators and operations associates, share science results with science, product, and tech partners and customers, and write science papers for submission to peer-review venues.
About the TeamWe are a team of applied scientists building AI/ML solutions to make Amazon the Earth's most trusted shopping destination for safe and compliant products. Our team is passionate about delivering scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while pursuing ambitious, long-term research.
Requirements- PhD, or Master's degree and 5+ years of applied research experience.
- Experience programming in Java, C++, Python, or related languages.
- Experience with neural deep learning methods and machine learning.
- Experience with conducting research in a corporate setting.
- Experience with large-scale machine learning systems such as integration and profiling of large-scale ML solutions.
- Experience with various AWS tools and services related to ML applications (Sagemaker, ECS, EMR,...).
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