Amazon

Senior Applied Scientist, Generative AI, Trust and Store Integrity Science

Seattle, WA
C++ Spark TensorFlow Java Python Deep Learning R NumPy Hadoop Machine Learning
Description
- 4+ years of applied research experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Deep expertise in computer vision, natural language processing and generative AI technologies
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Track record of leading large-scale AI transformation projects, and strong publication record in top-tier conferences/journals such as CVPR, NeuIPS, ICML, ACL, EMNLP

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
Amazon has built a reputation for excellence with recent examples of being named the #1 most trusted company for customers. To deliver on this reputation for trust, Selling Partner Abuse Prevention team is tasked with identifying and preventing abuse for our customers and brand owners worldwide.
Selling Partner Fraud and Abuse Prevention is hiring an Applied Scientist who will research and develop innovative machine learning based approaches to predict the near-term future. We are working on advanced research and we support Patent and publishing papers. The Scientist must understand deeply about Machine Learning methods and love extracting, nurturing and transforming high volume of data into actionable business information and making it readily accessible to stakeholders.

Key job responsibilities
• Lead the research, design, and implementation of innovative AI solutions for selling partner risk assessment and management
• Drive the technical vision for applying AI to transform workforce operations in Trust and Store Integrity organization
• Develop novel approaches to automate and enhance risk analysis processes using state-of-the-art language models
•Partner with business stakeholders to identify high-impact opportunities for AI-driven transformation
• Mentor and guide junior scientists while fostering a culture of innovation
• Design and implement evaluation frameworks to measure the impact of AI solutions
• Ensure responsible AI development with focus on fairness, transparency, and ethical considerations

About the team
Trust and Store Integrity Science is a new org established in 2024. We are missioned to leverage the fast evolving AI advancements to transform how we prevent bad actors in our stores, across science, engineering, product and program management, and operations.
Amazon
Amazon

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