Applied Scientist
- Design and implement innovative AI solutions across our three pillars: driving internal productivity, building the blueprint for how Audible works with AI, and unlocking new value through ML & AI-powered product features
- Develop machine learning models, frameworks, and evaluation methodologies that help teams streamline workflows, automate repetitive tasks, and leverage collective knowledge
- Enable self-service workflow automation by developing tools that allow non-technical teams to implement their own solutions
- Collaborate with product, design and engineering teams to rapidly prototype new product ideas that could unlock new audiences and revenue streams
- Build evaluation frameworks to measure AI system quality, effectiveness, and business impact
- Mentor and educate colleagues on AI best practices, helping raise the AI fluency across the organization
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- 2+ years of building machine learning models or developing algorithms for business application experience
- PhD in computer science, machine learning, engineering, or related fields, or experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience working with agile development methodologies
- Have publications at top-tier peer-reviewed conferences or journals
- Experience with application of frontier models and agentic frameworks to create (semi-) autonomous AI systems
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