About the job
As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems.
Responsibilities
Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
Push the boundary of innovation
Qualifications
Minimum
Knowledge of data structures, algorithm design, statistics, and system design
MSc + 5ys of relevant experience, or PhD +1 year in one of the following disciplines: Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
3+ years of experience in Deep Learning, Natural Language Processing/Understanding, GenAI and/or Reinforcement Learning
Proficiency in Python, SQL, and other scripting languages
Experience employing and innovating with LLMs/GenAI to solve complex problems
Preferred
deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation