As a member of the Reinforcement Learning team within Personalization, you will help create and innovate on the next generation of Recommendation and Personalization technologies on Amazon. Our team owns creating recommendation solutions that understand long-term customer shopping patterns and build on proven reinforcement learning techniques. Spanning Academia, research, and applied machine learning techniques operating at world-class scale, we focus on recommending the right product to the right customer at the right time. You will be surrounded by thought-leaders in the Personalization space who are patent-leaders within Amazon.
In Personalization we use state-of-the-art machine learning techniques and A/B testing to run experiments on some of Amazon’s most prominent and valuable pages. We work on a diverse range of products, building real-time, low-latency recommendation and ranking systems as well as building algorithms for understanding customer behavior and generating recommendations content. As a member of the team, you will work in a collaborative environment with a team of experienced engineers. You will have a unique opportunity to drive direct, measurable impact to our customers, powering features on multiple websites.
About our team: Our team has the autonomy to decide where we can have the most impact and get down to experimenting. We love metrics and the fast pace. We analyze data to uncover potential opportunities, generate hypotheses, and test them. We refuse to accept constraints, internal or external, and have a strong bias for action. We imagine, build prototypes, validate ideas, and launch follow-up experiments from the successful ones.
About you: You are an Applied Scientist with an interest in machine learning, data science, search, or recommendation systems. You have great problem solving skills. You love keeping abreast of the latest technology and use it to help you innovate. You have strong leadership qualities, great judgment, clear communication skills, and a track record of delivering great products. You enjoy working hard, having fun, and making history!
- PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
- 3+ years of experience in building machine learning models for business application
- Experience programming in Java, C++, Python or related language
- PhD and 7+ years of industry experience in one or more of Recommendation systems, Reinforcement learning, Machine Learning, Optimization.
- 5+ years of industrial experience in software development.
- Demonstrable experience in building, programming and integrating algorithms into production systems
- Proven experience producing computationally efficient software to meet real-time requirements.
- Understanding of the scientific theory behind machine learning techniques
- Understanding of practical considers that need to be addressed when applying machine learning techniques to customer problems