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ABOUT THIS ROLE
ABOUT YOU
As an applied scientist on our team, you will wear many hats and work in a highly collaborative environment that’s more startup than big company. You'll need to tackle complex problems that span a variety of domains: Machine learning, Artificial intelligence, Natural Language processing, real-time and distributed systems and help us build services and systems from the ground up which scale and serve billions of requests per day, with obsessively high reliability and low operational overhead. You'll have an opportunity to explore, innovate, invent and simplify various Playback state-of-art services and algorithms which leverage both custom and Industry proven Machine Learning, Natural Language processing and Artificial Intelligence technologies. Your work will focus on training and evaluating models and deploying them to production where we continuously monitor and evaluate. You'll work on large engineering efforts that solve significantly complex problems facing global customers. You'll be trusted to operate with independence and are often assigned to focus on areas with significant impact on audience satisfaction. You must be equally comfortable digging in to customer requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. We experiment a lot and it is a must to learn and be curios. You'll be encouraged to see the big picture, be innovative, and positively impact millions of customers.As a Senior Applied Scientist, you will...
- Understand large complex use cases across the Playback org and design scalable, efficient, and automated solutions
- Design, develop, and deploy state-of-art Optimization services & algorithms and novel adaptive bitrate algorithms
- Push the boundary of innovation
ABOUT AUDIBLE
- 5+ years of industry experience in Deep learning, Natural Language Processing/Understanding, Reinforcement learning and Speech processing
- PhD in one of the following disciplines: Computer Science, Machine Learning, Statistics, Data Science, Applied Math, Operational Research or a related quantitative field
- Fluency in Python, SQL or similar scripting languages and skilled at Java, C++, or other programing languages
- Experience in algorithm development
- Depth and breadth in state-of-the-art machine learning technologies
- Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud-platforms
- Big Data Engineering with Spark / AWS EMR & Glue
- Domain knowledge of comparable products (digital, retail)
- Publications at top-tier peer-reviewed conferences or journals in one of those areas (natural language processing/understanding, deep learning, machine learning, or speech processing)
- Proven track record of innovation in creating novel algorithms and advancing the state of the art
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