Sr. Applied Scientist, RISC - Seattle

Job Description

We are seeking an exceptional Sr. Applied Scientist to join a team of experts in the field of machine learning, and work together to tackle challenging problems across diverse compliance domains. We leverage and train state-of-the-art multi-modal and large-language-models (LLMs) to detect illegal and unsafe products across the Amazon catalog. We work on machine learning problems for multi-modal classification, intent detection, information retrieval, anomaly and fraud detection, and generative AI.

This is an exciting and challenging position to deliver scientific innovations into production systems at Amazon-scale to make immediate, meaningful customer impacts while also pursuing ambitious, long-term research. You will work in a highly collaborative environment where you can analyze and process large amounts of image, text and tabular data. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. There will be something new to learn every day as we work in an environment with rapidly evolving regulations and adversarial actors looking to outwit your best ideas.

Key job 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.

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
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

About the team
We are a team of applied scientists building AI/ML solutions to make Amazon Earth’s most trusted shopping destination for safe and compliant products.

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
- Experience with conducting research in a corporate setting

Preferred Qualifications:

- 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, ...)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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.