ABOUT THIS ROLE
As a Senior 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, artificial intelligence (AI), natural language processing (NLP), reinforcement learning (RL), real-time and distributed systems. Your primary focus will be on designing, developing, and deploying highly innovative modeling techniques to production to advance the state of the art in aforementioned domains. Your decision-making will consistently incorporate robust, data-driven business and technical judgment.
ABOUT YOU
You have a background in modern programming languages, distributed system design, service-oriented architecture, and high scalability. Experience in advanced machine learning technologies and Artificial intelligence is a big plus. Equally important is the ability to multi-task, invent, create reliable and maintainable code, and find creative, scalable solutions to difficult problems. You'll work with experienced managers who'll care for you. We'll guide you on your career growth path and there's no shortage of technical challenges.
As a Senior Applied Scientist, you will...
- Understand large complex use cases across the business and design scalable, efficient, automated model solutions
- Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features
- Drive and lead strategic initiatives to employ the most recent advances in ML/AI in a fast-paced, experimental environment
- Mentor and grow the scientists in the team and across Amazon
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
- 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
PREFERRED QUALIFICATIONS
- 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
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.