Preferred Networks | Deep Learning Researchers & Engineers | Tokyo | ONSITE, VISA, https://www.preferred-networks.jp/en/
We are a startup with ~200 members based in Tokyo, focusing on developing technology for Autonomous Driving, Robotics, and Bio-Healthcare. We love open source and are actively developing CuPy and the deep learning framework Chainer: https://github.com/cupy/cupy https://github.com/chainer/chainer Recently, we unveiled a personal robot system at CEATEC Japan 2018, exhibiting fully-autonomous tidying-up robots. https://www.preferred-networks.jp/en/news/pr20181015
We have one of the world’s largest private GPU clusters, with 1024 NVIDIA Tesla P100 and 512 V100 32Gb GPUs, and we are expanding it further with 1,024 NVIDIA V100 Tensor Core GPUs in July (https://www.preferred-networks.jp/en/news/pr20190318), and using our own custom DL chip MN-Core in 2020: https://www.preferred-networks.jp/en/news/pr20181212. Using our cluster we achieved the world record at that time of training on ImageNet in 15 minutes: https://www.preferred-networks.jp/en/news/pr20171110 Recently, we got the 2nd prize out of 454 teams in the Google AI Open Images - Object Detection Track challenge on Kaggle: https://www.preferred-networks.jp/en/news/pr20180907
We have a strong emphasis on research, and our technical advisors are Pieter Abbeel (UC Berkeley), Takeo Igarashi (the University of Tokyo), Kenji Fukumizu (the Institute of Statistical Mathematics) and Yarin Gal (University of Oxford). We continuously publish at top conferences like ICRA, ICCV, CVPR, ICLR, ICML, NIPS, NAACL, CHI, UIST, etc. Learn more about our research activities here: https://www.preferred-networks.jp/en/activities
So far we have raised over $100 million from Toyota, FANUC, Hakuhodo DYHD, Hitachi, Mizuho Bank, Mitsui & Co, Chugai Pharmaceutical and Tokyo Electron.
We have a western-style working environment with attractive salaries and benefits in the heart of Tokyo. Ability to communicate in either English or Japanese is OK. We are looking for talented individuals with skills in various areas related to cutting-edge deep learning applications in many industries. Find out more, and apply for all positions here: https://www.preferred-networks.jp/en/jobs
navenio | Research Engineer, SLAM Engineer, Machine Learning Engineer | Oxford, UK | Onsite Problem area: indoor localisation. GPS doesn't work indoors but indoor localisation has a huge range of applications so navenio develops smartphone based indoor localisation technology.
Why would you want to work here?
We are a team of competent engineers from a broad range of backgrounds who write modern C++ and Python 3 to solve interesting research problems. navenio is a spin out of Oxford University, we are well funded and have an academic culture. Engineers have ownership of projects and autonomy to develop the solution they choose. We use continuous integration and automated testing to move quickly and develop our technology. Our current largest market is healthcare, we work on a strongly ethical technology that improves quality of care for patients through increased efficiency while lowering healthcare costs for society.
What are we looking for?
Research engineer:
• People who like to write high quality Python and modern C++
• People with a track record of algorithm development
• Highly capable people from a range of backgrounds including (but not limited to): machine learning, signal processing, robotics or academic research
Technologies used: Research: C++17, Python 3, scikit learn.
R&D engineer: https://navenio.workable.com/j/2737E0B606