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Newark, New Jersey

Applied Scientist

Global Insights & Data Science   |   Job ID  2925199
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Job Summary

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.

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
- Apply and extend state-of-the-art LLM techniques to address specific customer or business needs at the project level
- Work on portions of systems, large components, applications, or services supporting machine learning and AI use cases
- Apply and extend state-of-the-art techniques in areas like NLP and deep learning to address specific customer or business needs
- Execute on team-level goals while creating intellectual property through your work
- Apply best practices in software development at the component level, ensuring solutions are testable, reproducible, and efficient
- Document and share findings that contribute to the internal and external scientific community
- Begin mentoring and developing teammates while gaining experience in tactical work and learning to be strategic
- Collaborate with tech and product teams to implement solutions that consider relevant tradeoffs at the component level

ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

Basic Qualifications

- 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

Preferred Qualifications

- Contributions to peer-reviewed publications that validate novelty in your field
- Experience applying LLMs to solve specific customer or business problems
- Experience creating intellectual property through invention or innovation Demonstrated ability to work with some autonomy while knowing when to seek direction
- Track record of documenting and sharing findings in line with scientific best practices
- Experience explaining complex scientific concepts to team members
- Domain knowledge of comparable products (digital, retail)
- Experience applying and extending existing scientific techniques to address specific customer needs

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.
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