IoT refers to a system of physical devices, from cars, light bulbs, sensor grids and more, that connect to the Internet. AWS IoT is revolutionizing industries and has emerged as a leading innovator in the interconnected device space. Our aim is to offer the most scalable, secure and robust IoT platform enabling industries and businesses to do more with less scaling to billions of devices and trillions of messages.
If you get excited about analyzing and modeling terabytes of data to solve real world problems, this is a job for you. We are looking for top scientists capable of using machine learning and other techniques to design, evangelize and implement state-of-the-art solutions for never-before-solved problems in IoT. Join us as we build completely new services that will touch every single device that is connected with AWS IoT.
As a Senior Applied Scientist with IoT, you will have a critical role in devising techniques that can work with high-noise data using significant analytical and machine learning skills and an ability to partner with thought leaders across Amazon.
A successful candidate will enjoy rigorous data analysis, and bring a good understanding of systems architecture to deliver practical and scalable solutions. Our applied scientists work closely with software engineers to put algorithms into practice. You will also mentor junior team members and educate leaders across the organization. Above all, a successful candidate will be a self-starter, have strong business judgement and customer obsession.
PhD in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
5+ years of hands-on experience in predictive modeling and analysis
Strong algorithm development experience
Skills with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language
Track record of peer reviewed academic publications.
Strong verbal/written communication skills, including an ability to effectively collaborate with both research and technical teams.
10+ years of relevant experience in industry and/or academia.
Extensive experience applying theoretical models in an applied environment.
Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods.
Strong Experience in Structured Prediction and Dimensionality Reduction.
Experience with defining organizational research and development practices in an industry setting