Brief Description:
AiFi is transforming the way Artificial Intelligence is used to solve the problems of today. Our software engineers are developing state-of-art technologies that change how machines perceive, communicate and interact with the world. Our solutions handle information at a huge scale, which extends beyond simple images or video. We offer scalable distributed HW and SW solutions that address and grow with our customers’ needs.
As a Research Engineer in AiFI’s Edge Computing team, you will work on deep learning speedup, performance optimization and embedded device. You will design efficient neural network architectures for various tasks including object detection and action recognition.
Btw, we are in the final around of Nvidia's Inception Award. Check out the news: http://bit.ly/2HxBiBg Join us @GTC18!
If you love:
- To optimize deep learning speed and performance on embedded devices
- To design efficient neural network architectures
- To implement highly optimized code for fast execution
- To design API SDK
We are seeking someone with:
- With at least a BS Degree in Computer Science, Computer Engineering or relevant technical field
- Strong experience in Algorithmics
- Good understanding of deep learning
- Strong C++ and Python programming skills
- Ability to write clear, well-documented, high-performance code
- Experience using Git, or other version control software
If you have one of these experience it is even better:
- Assembly - x86 or ARM
- Experience with OpenGL/Metal/OpenCL is a plus
- Experience in optimizing inference time of neural networks on embedded devices
Our Recruitment Process
We aim to reply to all applicants within a week of receiving your application. Our interview process consists of several stages, each one allowing us get to know you better, professionally and technically. It is also an opportunity for you to gain a better understanding of our culture and the work we do here at AiFi.
The stages include:
- CV and open source code / public portfolio review: make sure that you include the code examples because that will give us enough confidence to skip the code test to save your time
- The Written Exercise - We sometimes skip this if your code examples looks good
- Phone Interview - Usually one hour via Google Hangout/Skype
- Onsite Interview - Come and meet our team in Santa Clara
by via developer jobs - Stack Overflow
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