FAQs
What is the primary focus of a Senior Applied Scientist at Audible?
The primary focus is on designing, developing, and deploying highly innovative modeling techniques in domains such as machine learning, AI, NLP, reinforcement learning, and real-time systems to solve complex business problems.
What qualifications are required for this position?
The position requires 5+ years of industry experience in deep learning, NLP/understanding, reinforcement learning, and speech processing, as well as a PhD in disciplines like Computer Science, Machine Learning, Statistics, or a related field.
What programming languages are necessary for this role?
Fluency in Python, SQL, and experience with Java, C++, or similar programming languages are necessary for the role.
What type of experience is preferred for candidates applying for this position?
Preferred experience includes domain knowledge of comparable products, publications at top-tier peer-reviewed conferences, and a proven track record of innovation in machine learning algorithms.
Will I have opportunities for career growth in this role?
Yes, you will work with experienced managers who will guide you on your career growth path, ensuring you have access to opportunities for professional development.
Is mentoring a part of the responsibilities for this position?
Yes, a Senior Applied Scientist is expected to mentor and grow scientists within the team and across the organization.
What technologies will I be working with?
You will work with technologies related to machine learning pipeline orchestration using AWS services like SageMaker, Batch, Lambda, and Step Functions, as well as big data engineering with Spark and AWS EMR & Glue.
What type of collaborative work will I be involved in as a Senior Applied Scientist?
You will work closely with teams of scientists and software engineers to drive real-time model implementations and deliver impactful features.
How does Audible view diversity in the workplace?
Audible believes that employing a diverse workforce is central to their success and values recruiting decisions based on experience and skills.