Key job responsibilities
As part of the AGI team, an Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more. An Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology.
A day in the life
An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice.
The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions. They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 1+ years of building models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with Large Language Models (LLMs) or multimodal architectures
PREFERRED QUALIFICATIONS
- PhD degree in Mathematics, Statistics, Engineering, Machine Learning, Computer Science or related discipline
- 4+ years of industry or postdoctoral experience in machine learning
- Experience with patents or publications at top-tier peer-reviewed conferences or journals
- Experience with popular deep learning frameworks including MxNet, PyTorch or TensorFlow
- Experience in building large-scale machine learning systems
- Proficiency in state-of-the-art Natural Language Processing (NLP) and Computer Vision (CV) deep learning models
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 $136,000/year in our lowest geographic market up to $222,200/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.