Job Description
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
Audible is seeking a Senior Product Manager, AI Content Discovery to define and build critical experiences that will help the right users find the right content at the right time. As part of the Content Discovery team, which encompasses Search, Personalization and Browse, you will leverage AI technologies to connect listeners with content they love. Your mission will be to build features that delight every Audible member by making content discovery intuitive, effortless, and compelling.
ABOUT YOU
You're a continuous learner with a commitment to action and an attitude that anything is possible. You execute cross-functional projects with a relentless customer focus. An accountable, hands-on problem-solver, you let nothing stand in your way. With strong problem-solving skills, deep product management experience, and an understanding of ML/AI-powered content discovery systems, you excel at communication and data-driven decision-making. Ready to engage with engineering teams, you work cross-functionally to solve complex discovery problems. If you love rolling up your sleeves, getting stuff done, and have a passion for AI-driven content discovery in the media industry, this role is for you.
As a Senior Product Manager, AI Content Discovery, you will...
- Define and execute the roadmap with clearly articulated and well-measured goals, contributing to the worldwide Content Discovery product strategy
- Develop and execute strategies to enhance personalized content discovery experiences, leveraging AI and machine learning techniques to connect users with relevant content based on their unique preferences and behaviors
- Build with an AI-first mindset, championing the latest innovations in GenAI technology and implementing them in content discovery experiences
- Lead cross-functional collaboration with engineering, data science, and UX teams to create discovery experiences that are meaningful, delightful, and driven by advanced AI algorithms.
- Work with data science teams to evaluate AI/ML models choices and determine tradeoffs between performance and efficiency
- Design and implement personalization features that empower customers to shape their experience, connecting them with content they'll love based on their listening patterns
- Drive understanding across Audible of the impact and potential of AI-powered discovery initiatives, championing data-driven insights to bolster content engagement
- Measure and analyze the performance of AI/ML-powered discovery features against business objectives, continuously optimizing and refining models
- Interpret insights and translate complex technical concepts into clear product requirements documents for engineering teams
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
- Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
- 5+ years of experience in consumer product management, with 1+ year in complex organizations
- Experience in data driven hypothesis testing and experimentation
- Experience working with design teams to improve the user experience for customer facing products/features
PREFERRED QUALIFICATIONS
- 3+ years of relevant professional experience in a consumer-facing machine learning oriented product management role
- Experience with generative AI, large language models, and their applications in customer-facing experiences
- Experience implementing AI/ML solutions for search, browse, or content recommendation features
- Content streaming/media/entertainment industry experience (books, music, movies, etc.)
- Ability to evaluate and recognize the benefits and limitations of various AI/ML models
- Strong data analytics and interpretation skills
- Experience with rapid prototyping of AI-driven features and conducting A/B tests
- Team player: Strong, demonstrated ability to rally and bring varying functional teams together
Amazon 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. 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 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 $136,100/year in our lowest geographic market up to $235,200/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 . This position will remain posted until filled. Applicants should apply via our internal or external career site.
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