Amazon's Discovery Tech organization needs to help customers discover the hottest and best-reviewed products by building new customer-facing features and experiences. The Recommendations team is responsible for creating and building critical services that automatically generate personalized product recommendations in real-time, leveraging machine-learning and statistical models to deliver the best possible shopping experience.
Requirements
- Experience programming or scripting language like Python, Java, C or C++
- Experience with popular deep learning frameworks such as MxNet and Tensor Flow
- Experience in solving business problems through machine learning, data mining and statistical algorithms
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Responsibilities
- creating and building critical services that automatically generate, in real time, personalized product recommendations presented to Amazon customers worldwide
- leverage machine-learning and statistical models to deliver the best possible shopping experience
- design, development, testing, and deployment of data-driven and highly scalable machine learning solutions in product recommendation
- set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms
- Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility
- tackle intrinsically hard problems, acquiring expertise as needed
- decompose complex problems into straightforward solutions
Other
- PhD in math/statistics/engineering or other equivalent quantitative discipline
- analytical problem solvers who enjoy diving into data
- excited about data science and statistics
- can multi-task
- can credibly interface between engineering teams and business stakeholders
