Senior Applied Scientist, FinTech ATARI

Description

At Amazon's FinTech organization, we are seeking a Senior Applied Scientist to spearhead the development of cutting-edge Generative AI applications that will redefine the financial services industry. You will harness the transformative power of Large Language Models (LLMs) and multi-agent architectures to drive disruptive innovation across Finance domains such as fraud prevention, financial forecasting, and insurance. Because of our scale, your products will have hundreds of millions of dollars of impact.

You will collaborate closely with cross-functional business and engineering teams to identify and deliver high-impact use cases for Generative AI. You will design, develop, and evaluate Generative AI models and agents. You will partner with engineering teams to ensure seamless model deployment and integration into production systems, while also driving continued scientific innovation as a published thought leader and practitioner.

You will mentor and develop junior scientists and engineers, fostering a culture of continuous learning and improvement. You will contribute to the broader research community by publishing your work in peer-reviewed conferences and journals.

Check out this AWS Blog for some of our recent work in LLMs for financial application: https://aws.amazon.com/blogs/machine-learning/efficient-continual-pre-training-llms-for-financial-domains/

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in our careers.

Basic Qualifications

• PhD, or Master's degree and 6 years of applied research experience
• 5 years of building machine learning models for business application experience
• Experience programming in Java, C , Python or related language
• Experience with neural deep learning methods and machine learning
  
  

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Track record of publications in top-tier machine learning conferences or journals
  
  

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.

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.


Company - Amazon.com Services LLC

Job ID: A2735003