Senior Applied Scientist, Product Knowledge

$150,400 - $260,000/Yr

Amazon - Seattle, WA

Full-time - Senior

Seattle, WA

10,001+ employees

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Senior Applied Scientist, Product Knowledge at Amazon is responsible for leading the development of advanced AI models that enhance the eCommerce ontology, which serves as the authoritative source of product knowledge. This role involves solving complex problems related to product classification, attribute extraction, and scalable knowledge services, all while working with vast and diverse data sources. The position is ideal for individuals passionate about innovation in machine learning and natural language processing, aiming to improve customer experiences at scale.

Responsibilities

• Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology at scale.
• Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources.
• Collaborate with engineers to design and implement robust services.
• Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge.
• Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing.
• Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community.
• Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields.

Requirements

• 4+ years of applied research experience.
• 3+ years of building machine learning models for business application experience.
• PhD, or Master's degree and 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Nice-to-haves

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

Benefits

• Competitive salary based on market location and experience.
• Equity and sign-on payments as part of total compensation package.
• Full range of medical, financial, and other benefits.