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Description

The Amazon Regulatory Intelligence, Safety, and Compliance (RISC) team is seeking an exceptional Applied Scientist to tackle complex compliance challenges. In this high-impact role, you will leverage your deep technical expertise and customer-obsessed mindset to design and evaluate state-of-the-art algorithms in risk modeling, computer vision, and natural language processing.

You will translate complex business requirements into well-defined science problems and work collaboratively with product, engineering, and business stakeholders to drive real-world impact. Staying at the forefront of applied machine learning, you will continuously adapt your skills to tackle new challenges.

Contributing to Amazon's scientific thought leadership, you will author high-quality research papers for internal and external conferences. This is an opportunity to apply your technical skills in a fast-paced, highly collaborative environment, making a meaningful difference in the lives of Amazon's customers.

If you have a passion for solving complex problems and a customer-centric approach, we encourage you to apply for this exciting role.

Key job responsibilities

- Explore the use of reinforcement learning, multi-agent systems, and meta-learning to build autonomous AI agents that can adapt to new challenges and support complex decision-making.

- Design and evaluate state-of-the-art algorithms and approaches in risk modeling, using techniques such as graph neural networks, deep learning, and boosted trees to detect anomalies, fraud, and policy violations.

- Develop advanced multi-modal and large language models to classify product content, understand customer intent, and retrieve relevant information.

- Collaborate closely with product managers, engineers, and business stakeholders to validate hypotheses, drive adoption, and maximize the real-world impact of your work.

- Translate complex product and customer experience requirements into well-defined, measurable science problems and KPIs, contributing to Amazon's scientific thought leadership through high-quality research papers.

A day in the life

- 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

- Contributing to team retrospectives for continuous improvements

- Participating in science research collaborations and attending study groups with scientists across Amazon

Basic Qualifications

- 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

Preferred Qualifications

- 7+ years of building machine learning models for business application experience

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.