Audible
Lead Software Development Engineer, AI/Machine Learning
Audible, Newark, New Jersey, us, 07175
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 a Lead Software Engineer - AI/ML, it's up to you to design, architect, and implement machine learning solutions that drive transformative technological advancements. The ideal candidate will combine deep technical expertise with strategic thinking, capable of translating complex business challenges into scalable, intelligent systems.
ABOUT THE TEAM Our AI/ML Engineering team is at the forefront of transformative technological innovation, dedicated to solving complex challenges through intelligent system design. We are a dynamic, collaborative group of technologists who push the boundaries of machine learning, artificial intelligence, and large-scale distributed systems. Our mission is to develop AI solutions that drive technological breakthroughs, deliver measurable business impact, create intelligent systems that learn, adapt, and evolve.
ABOUT YOU As a Lead Software Engineer - AI/ML, you will be responsible for designing and developing advanced machine learning architectures and intelligent systems.
Design and develop advanced machine learning architectures and intelligent systems
Create robust, scalable ML infrastructure and pipelines
Develop end-to-end AI solutions addressing complex technical and business challenges
Architect machine learning models with a focus on performance, scalability, and efficiency
Conduct advanced research and prototype innovative AI/ML approaches
Collaborate cross‑functionally to align technical solutions with strategic objectives
Mentor junior engineers and contribute to technical knowledge sharing
Lead technical design reviews and provide architectural guidance
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.
5+ years of non‑internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience as a mentor, tech lead or leading an engineering team
Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
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ABOUT THIS ROLE As a Lead Software Engineer - AI/ML, it's up to you to design, architect, and implement machine learning solutions that drive transformative technological advancements. The ideal candidate will combine deep technical expertise with strategic thinking, capable of translating complex business challenges into scalable, intelligent systems.
ABOUT THE TEAM Our AI/ML Engineering team is at the forefront of transformative technological innovation, dedicated to solving complex challenges through intelligent system design. We are a dynamic, collaborative group of technologists who push the boundaries of machine learning, artificial intelligence, and large-scale distributed systems. Our mission is to develop AI solutions that drive technological breakthroughs, deliver measurable business impact, create intelligent systems that learn, adapt, and evolve.
ABOUT YOU As a Lead Software Engineer - AI/ML, you will be responsible for designing and developing advanced machine learning architectures and intelligent systems.
Design and develop advanced machine learning architectures and intelligent systems
Create robust, scalable ML infrastructure and pipelines
Develop end-to-end AI solutions addressing complex technical and business challenges
Architect machine learning models with a focus on performance, scalability, and efficiency
Conduct advanced research and prototype innovative AI/ML approaches
Collaborate cross‑functionally to align technical solutions with strategic objectives
Mentor junior engineers and contribute to technical knowledge sharing
Lead technical design reviews and provide architectural guidance
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.
5+ years of non‑internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience as a mentor, tech lead or leading an engineering team
Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
#J-18808-Ljbffr