Amazon

Applied Scientist II, Amazon Payment Products (L5)

Job Description

Are you passionate about building data-driven applied science solutions to drive the profitability of the business? Are you excited about solving complex real world problems? Do you have proven analytical capabilities, exceptional communication, project management skills, and the ability to multi-task and thrive in a fast-paced environment? Join us an Applied Scientist to deliver applied science solutions for Amazon Payment Products. Amazon Payment Products team creates and manages a global portfolio of payment products, including co-branded credit cards, installment financing, etc. Within this team, we are looking for an Applied Scientist who will be responsible for the following:

Key job responsibilities
As an Applied Scientist, you will be responsible for designing and deploying scalable ML, GenAI, Agentic AI solutions that will impact the payments of millions of customers and solve key customer experience issues. You will develop novel deep learning, LLM for task automation, text processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to file for patents and/or publish research work where opportunities arise. As the Payment Products organization deals with problems that are directly related to payments of customers, the Applied Scientist role will impact the large product strategy, identify new business opportunities and provides strategic direction, which will be very exciting.- Master's degree, or PhD and 5+ years of practical machine learning experience
- Master's degree, or a PhD and experience building machine learning models or developing algorithms for business application
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience that includes strong analytical skills, attention to detail, and effective communication abilities, or experience troubleshooting and debugging technical systems
- Experience in delivering design solutions for projects of large scope and complexity
- Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership


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