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 Senior Manager, Applied Science, you will manage high-performing research teams. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams as well as business stakeholders to maximize velocity and impact of your team's contributions.
ABOUT YOU You drive the technical vision and strategy for your team while fostering a culture of innovation and scientific excellence. You lead a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking.
As a Senior Manager, Applied Science, you will...
- Lead and manage teams of applied scientists and machine learning engineers, providing mentorship, career development, and performance management
- Define and execute the technical roadmap for applied science initiatives, balancing innovation with business impact
- Work with new technologies and methodologies that improve model performance, usability, and scalability of ML systems
- Translate complex business requirements into technical deliverables and deliver operationally stable solutions that provide exceptional customer experiences
- Participate in the full development cycle, end-to-end, from research and design to implementation, testing, documentation, delivery, and maintenance
- Evaluate and make strategic decisions around the use of new or existing ML frameworks, tools, and technologies
- Collaborate with Senior Engineers, Principal Engineers, and Principal Scientists across the organization to define architecture and research plans for the next three years
- Drive scientific rigor through experimentation, A/B testing, and data-driven decision making Partner with cross-functional teams including product management, engineering, and business stakeholders to align science initiatives with business objectives
- Publish research findings and represent Amazon at top-tier conferences and in the scientific community
- Establish best practices for ML development, including model evaluation, monitoring, and continuous improvement
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
- Master's degree or above in computer science, machine learning, engineering, or related fields, or Associate's degree or above
- 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track
Preferred Qualifications
- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
- 10+ years of practical work applying ML to solve complex problems for large-scale applications experience
- 5+ years of people management experience
- Experience leading, mentoring and growing teams of scientists (teams of five or more scientists)
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
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