Description de l'offre
Machine Learning is changing how Amazon operates, from Drones, Robotics to stores without checkout lines. The AWS AI team focuses on solving challenging ML problems by providing general-purpose tools. Are you passionate about Deep Learning, Machine Learning and Artificial intelligence?
The team is part of the Apache MXNet developer community. Apache MXNet is an open-source deep-learning framework, endorsed by Amazon Web Service (AWS). The core responsibilities of this role will be across the deep learning stack from core algorithmic contributions to applications. You will engage with Amazon-internal teams on their advanced deep learning use-cases via engineering and algorithms, you will help develop and operate the benchmarking of deep learning frameworks along a number of metrics, including energy efficiency on edge devices and build applications on top of MXNet.
We are looking for an outstanding individual who combines technical, communication, and analytical capabilities with a demonstrated ability to get the right things done quickly and effectively.
You are comfortable working with a team of software development engineers and applied scientists. Given the cross Amazon nature of our products and this particular setting within an Apache Incubator project, you should be highly self-motivated and self-directed having good cross-team collaboration skills.
The ideal candidate for our team is a thinker and a doer: someone who embraces infrastructure and automation, and is motivated by the prospect of engineering excellence balanced with a healthy sense of pragmatism.
You will have exciting and challenging responsibilities like:
· Learn, use and optimize performance of advanced technologies, viz. Data Science, Deep Learning frameworks, Distributed Systems, work with Anaconda, MXNet, Keras, Docker, Jenkins, etc.
· Create innovative products using advanced technologies, and see them launched in high-volume production within Amazon and with Amazon customers.
· Collaborate with internal engineering teams, technology companies around the world and open source community.
· PhD or Master's Degree in Computer Science or Engineering.
· 4+ years of software development, validation and deployment experience.
· 2+ years of experience in programming parallel and distributed systems
· 2+ years of experience debugging low-level problems, performance analysis and optimizations.
· Expertise in C++ 11/14/17
· Expertise in Python or programming languages used in Machine Learning.
· Deep technical expertise in operating systems, distributed systems, high-performance computing and cloud infrastructure.
· Developer experience with Machine Learning or Deep Learning frameworks and applications.