Applied Scientist, FinTech ATARI
DESCRIPTION
At Amazon's FinTech organization, we are looking for an Applied Scientist to spearhead the development of 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.
Key job responsibilities
As an Applied Scientist on our team, you will be responsible for the research, design, development and evaluation of Generative AI models and agents. You will play a critical role in driving the development of LLM-based multi-agent architectures that automate complex workflows to delight our customers. You will handle Amazon-scale use cases with significant impact on our customers’ experiences. You will collaborate closely with cross-functional science, engineering and business partners to identify and deliver high-impact use cases for Generative AI. 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/
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 solving business problems through machine learning, data mining and statistical algorithms
- 1+ years of building models for business application experience
PREFERRED QUALIFICATIONS
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- Experience developing and implementing deep learning algorithms, particularly with respect to natural language processing
- Track record of publications in top-tier machine learning conferences or journals
- Excellent communication skills, solid work ethic, and a strong desire to write production-quality code.
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 $136,000/year in our lowest geographic market up to $223,400/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.