Software Development Engineer Machine Learning Audible

At Audible we believe stories have the power to transform lives. Its why we work with some of the worlds 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
This opportunity is for a Software Development Engineer for Audibles Machine Learning Engineering (MLE) team to drive initiatives on the leading edge of Machine Learning (ML) Large Language Models (LLMs) personalization and content discovery. MLE is an enabling team that works alongside our applied science teams to train productionize monitor and deploy machine learning models on a massive worldwide scale. These models help Audible customers find their next listen and are central to everything from the recommendations listeners see to the structure and content of their home screen.

MLEs platforms run the gamut from data pipelines that serve tens of thousands of requests for realtime lowlatency data per second to internal tools that leverage LLMs for process automation and productivity. As a member of the MLE team youll be working on infrastructure that is core to the listener experience and helping to shape how Audible and Amazon build monitor and deploy LLMs for production usecases. Our engineers use a mix of software engineering and machine learning skills to build massively scalable highavailability systems that allow our internal partners and customers to experiment more quickly retrain and refresh recommender models and respond to changing patterns of user behavior.

Achieving this vision means continuously innovating enhancing the tools and strengthening our development process how we work and leveraging new technologies to deliver services. We need your help to develop and deliver on this global vision.

ABOUT YOU
You are a skilled communicator who can tailor their message to ensure clarity and understanding among a variety of stakeholders. You possess a detailoriented approach to problemsolving relishing the opportunity to dig deep and find the best solutions to challenges. You are curious and unafraid to ask questions in order to gain a deeper understanding of complex issues. You are flexible and collaborative team player who always strives to bring their best to every interaction inspiring others to do the same. You are passionate about bringing their skills to Audible while remaining open and eager to learn new things.

As a Software Development Engineer Machine Learning you will...
Drive the direction of our technical solutions across disciplines varying from deep learning embeddings LLMs data pipelines and realtime ML serving systems
Design develop and production software to support scalable offline machinelearning pipelines and online serving components
Work closely with applied scientists to optimize the performance of machinelearning models improve the teams machine learning productivity and advance the technical foundation to empower our science innovation.

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.

3 years of noninternship professional software development experience
2 years of noninternship design or architecture (design patterns reliability and scaling) of new and existing systems experience
Bachelors degree in computer science or equivalent

3 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
Experience in machine learning information retrieval statistics or natural language processing.

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