Are you interested in big data, machine learning, LLM, and product recommendations? If so, Amazon's Personalization team might be the right place for you.

About our organization:
We are part of Amazon’s Personalization organization, a high-performing group with a huge impact on hundreds of millions of customers, innovating at the intersection of customer experience, machine learning, and large-scale distributed systems. We run global experiments and our work has revolutionized e-commerce with features such as "Compare with similar items", "Keep shopping for ...", “Customers who bought this item also bought”, and, “Frequently bought together” among others.

Amazon’s internal surveys regularly recognize us as one of the best organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.

About you:
You are a Sr. Applied Scientist who love big data and passionate about improving customer shopping experience by inventing and applying state-of-art technologies (e.g., LLM, Machine Learning, NLP, and Computer Vision) to build the next-generation product recommendation engine for Amazon. You have an entrepreneurial spirit, know how to deliver, are deeply technical and highly innovative. You work closely with software engineers to put algorithms into production. You also work in partnership with teams across Amazon to create enormous benefits for our customers. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of cutting edge products used every day by people you know.


Key job responsibilities

- Use machine learning and analytical techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes
- Design, development and evaluation of highly innovative models for predictive learning
- Work closely with software engineering teams to drive model implementations and new feature creations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Research and implement novel machine learning and statistical approaches
- Mentor junior scientists; review their work and provide feedback

About the team
Our mission is to delight every Amazon customer with a personalized shopping experience. We achieve our mission through investments in large-scale machine learning and distributed system solutions with the purpose of delivering the future of shopping on Amazon. Our solutions help customers explore product categories, discover high quality products that meet their needs, and provide most relevant information to help customers make confident shopping decisions. We are seeking an Applied Scientist to make step function improvements in creating a delightful shopping 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- 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.

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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.