About this role
Summary: Join the Trust and Store Integrity Science Team to build advanced machine learning systems that prevent eCommerce fraud and protect millions of transactions. You will design end-to-end ML solutions, leverage GenAI/LLM technologies, and collaborate with engineering teams to drive profitability and customer experience.
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?
If yes, then you may be a great fit to join the Amazon Selling Partner Trust & Store Integrity Science Team. We are looking for a talented scientist who is passionate to build advanced machine learning systems that help manage the safety of millions of transactions every day and scale up our operation with automation.
Key job responsibilities
- Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations
- Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value
- Learn, explore and experiment with the latest machine learning advancements to create the best customer experience
A day in the life
You will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence.
You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.
You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
Basic qualifications
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- 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 - 142,800.00 - 193,200.00 USD annually