Job Description

• 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


"Amazon Science gives you insight into the company's approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It's the company's ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work."



Please visit https://www.amazon.science for more information



Amazon Business is one of Amazon's fastest growing businesses, focused on enabling business customers to research, discover and buy business, industrial and scientific products in large catalogs. Our customers include individual professionals, businesses and institutions that buy products in bulk quantities to run their business smoothly. Business customers have different and more complex needs than the traditional Amazon customer base. We operate in the US, EU5, Canada, Japan and India. And we are continually expanding to new countries.



We are looking for Applied Scientist with strong technical experience, who are passionate in building scientific driven solutions to be part of the Amazon Business organization. This is a great opportunity to innovate and provide the best customer experience in the entire journey of purchase, right from product discovery to post purchase experiences. This is your chance to make an impact of multi-trillion-dollars on your own.



In this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Software Engineers, Data Engineers, and other Applied Scientists, to build new and enhance existing ML models to optimize customer experience. A successful Applied Scientist at Amazon has extreme bias for action and operates in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and natural language processing (NLP) techniques to improve our customers' experience when using AB.



We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career."



Key job responsibilities



• Serve as a technical expert and leader in building new and enhancing existing ML models to optimize customer experience for Amazon Business
• Work closely with cross-functional teams including Product Managers, Software Engineers, Data Engineers, and other Applied Scientists
• Identify data requirements, build methodology, and develop statistically grounded tools and solutions using machine learning (ML) and LLM
• Drive projects from ideation to execution with an emphasis on bias for action.
• Stay up-to-date with the latest advancements in AI/ML and proactively identify opportunities to improve the customer experience


A day in the life



• Collaborate with product and engineering teams to understand business requirements and translate them into technical solutions
• Conduct in-depth data analysis and feature engineering to build robust ML models
• Prototype and test new ideas, iterate quickly, and deploy models to production
• Monitor model performance, troubleshoot issues, and continuously optimize models
• Share learnings and best practices with the broader team, contribute to innovation and publish research papers.
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
• Experience in professional software development