Amazon Applied Scientist 

United States, New Jersey, Newark 

983544334

ABOUT THIS ROLE
As an Applied Scientist II, you will work on complex problems where neither the problem nor solution is well defined. You'll define and crisply frame research problems while developing novel scientific techniques in domains including machine learning, artificial intelligence (AI), natural language processing (NLP), large language models (LLMs), reinforcement learning (RL), and audio processing. Your primary focus will be on applying and extending existing scientific techniques, as well as inventing new approaches to address specific customer needs and business problems at the project level. You will contribute to internal or external peer-reviewed publications that validate the novelty of your work, while documenting and sharing findings in line with scientific best practices. You will work on LLM applications to enhance Audible's customer experience We work in a highly collaborative environment where you'll primarily influence your team, begin mentoring more junior scientists, and partner with engineers and product managers to implement scalable, efficient approaches for difficult problems. You will operate with some autonomy while knowing when to seek direction to deliver high-quality scientific artifacts.As an Applied Scientist II, you will...
- Define and implement scalable, efficient approaches for difficult problems related to audio storytelling and content experiences- Work on portions of systems, large components, applications, or services supporting machine learning and AI use cases
- Apply best practices in software development at the component level, ensuring solutions are testable, reproducible, and efficient
ABOUT AUDIBLE

- 5+ years relevant experience + MS in one of the following disciplines: Computer Science, Statistics, Data Science, Economics, Applied Math, Operational Research or a related quantitative field OR PhD
- Industry experience in Deep Learning, Large Language Model, Natural Language Processing/Understanding, Reinforcement Learning, or Speech Processing
- Experience working with Large Language Models (LLMs) and their applications
- Fluency in Python, SQL or similar scripting languages and knowledge of Java, C++, or other programming languages
- Deep understanding of state-of-the-art scientific principles and techniques in at least one computer science discipline
- Experience with machine learning pipeline tools such as AWS SageMaker
- Ability to work with big data tools such as Spark, AWS EMR & Glue
- Experience defining and implementing solutions for difficult problems that require consideration of relevant tradeoffs