Senior Applied Research Scientist
19 hours ago
We are seeking a highly skilled Senior Applied Research Scientist to join our Compliance Shared Services team at Amazon Services LLC. As a key member of our team, you will be responsible for extending and inventing state-of-the-art research in multi-modal architectures, large language models, and federated learning paradigms.
Key Responsibilities- Design and evaluate state-of-the-art algorithms and approaches in multi-modality fusion, large language models, continual learning, and federated learning.
- Extend and invent new algorithms and scientific approaches that improve on the state-of-the-art to decrease Amazon's cost to serve.
- Collaborate with product and tech partners and customers to validate hypothesis, drive adoption, and increase business impact.
- Lead cross-organization working groups to develop science foundational capabilities applicable to multiple use cases beyond compliance for the broader Customer Trust and Selling Partner Services (SPS) organizations.
As a Senior Applied Research Scientist, you will be responsible for:
- Understanding customer problems, project timelines, and team/project mechanisms.
- Proposing science formulations and brainstorming ideas with team to solve business problems.
- Writing code, and running experiments with re-usable science libraries.
- Reviewing labels and audit results with investigators and operations associates.
- Sharing science results with science, product and tech partners and customers.
- Writing science papers for submission to peer-review venues, and reviewing science papers from other scientists in the team.
- Contributing to team retrospectives for continuous improvements.
- Driving science research collaborations and attending study groups with scientists across Amazon.
We are a combined team of applied scientists and ML engineers looking to not just solve our immediate Compliance problems but also generalize our solutions across Amazon and external customers.
Requirements- PhD, or Master's degree and 5+ years of applied research experience.
- Experience programming in Java, C++, Python or related language.
- Experience with neural deep learning methods and machine learning.
- Experience with conducting research in a corporate setting.
- Proficiency in developing re-usable Python libraries.
- Peer-reviewed publications in multi-modality, large language models, continual learning and/or federated learning.
- Ability to convey Machine Learning concepts and considerations to non-experts.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability.
- Experience leading long-term science direction, developing medium-term hypothesis plans, and short-term execution and delegation across 6+ scientists in science teams.
- Significant citations in peer-reviewed scientific contributions in relevant fields.
- Practical work experience in building, iterating, deploying and maintaining re-usable python libraries code in end-to-end production systems.
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