Applied Scientist Intern

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 ROLEAs an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI), Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. You will be at the forefront of transforming how Audible harnesses the power of AI to enhance productivity, unlock new value, and reimagine how we work. In this unique role, you'll apply ML/AI approaches to solve complex real-world problems while helping build the blueprint for how Audible works with AI. ABOUT YOUYou are passionate about applying scientific approaches to real business challenges, with deep expertise in Machine Learning, Natural Language Processing, GenAI, and large language models. You thrive in collaborative environments where you can both build solutions and empower others to leverage AI effectively. You have a track record of developing production-ready models that balance scientific excellence with practical implementation. You're excited about not just building AI solutions, but also creating frameworks, evaluation methodologies, and knowledge management systems that elevate how entire organizations work with AI.As an Applied Scientist, you will...- Design and implement innovative AI solutions across our three pillars: driving internal productivity, building the blueprint for how Audible works with AI, and unlocking new value through ML & AI-powered product features- Develop machine learning models, frameworks, and evaluation methodologies that help teams streamline workflows, automate repetitive tasks, and leverage collective knowledge- Enable self-service workflow automation by developing tools that allow non-technical teams to implement their own solutions- Collaborate with product, design and engineering teams to rapidly prototype new product ideas that could unlock new audiences and revenue streams- Build evaluation frameworks to measure AI system quality, effectiveness, and business impact- Mentor and educate colleagues on AI best practices, helping raise the AI fluency across the organizationABOUT AUDIBLEAudible 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- Experience programming in Java, C++, Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse- Currently enrolled in a Master's or PhD program in Computer Science, Machine Learning, Statistics, NLP, or a related quantitative field- Coursework or project experience in at least one of: NLP, recommender systems, machine learning, or deep learning- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, HuggingFace)- Experience implementing algorithms using both toolkits and self-developed codePREFERRED QUALIFICATIONS- Experience implementing algorithms using both toolkits and self-developed code- Have publications at top-tier peer-reviewed conferences or journals- Are enrolled in a PhD- Hands-on experience with LLMs, RAG pipelines, or fine-tuning (LoRA, PEFT)- Experience building or evaluating recommendation systemsAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.Our inclusive culture empowers Amazonians to deliver the best results for our customers.

Created: 2026-05-08