Publish 2017 PFN Internship Coding Tasks
* Japanese blog is also written here.
Preferred Networks (PFN) organizes two-month-long summer internship program for students in August and September every year.
The number of applications is increasing year by year. This year we have received the highest number of applications ever and the interview and selection process has been finished.
・PFN 2017 Summer Internship Program
Then we have published our intern coding tasks on github.
PFN is growing rapidly due to the increase attention to deep learning technology, and now many people with diverse background and various speciality are joining. When we considered research themes for 2017 PFN internship, lots of candidate topics came up. Therefore, we decided to look for interns not only on machine learning research but also on frontend, backend and chip development from this year.
We have received applications more than last year, both from Japan and the rest of the world, thanks to the promotion such as PFN Open House in Tokyo.
As the number of accepted intern students is also the largest ever, we are a bit worried that the office might be too packed after the internship starts in August 🙂
Since PFN focuses on the technology, we set up coding tests to evaluate the applicants’ basic knowledge about computer science, programming skills, and the ability to solve problems in their fields.
As written in the above, we have prepared problems for machine learning, frontend, backend and chip development categories (written in both English and Japanese), where each problem is reviewed by PFN engineers and researchers.
In addition to last year’s blog post (in Japanese), we have released all of the coding tasks since 2011 on github.
- PFN intern coding tasks：https://github.com/pfnet/intern-coding-tasks
The problems of this year consist of
- Machine learning and mathematics – Reinforcement learning, cartpole, cross entropy method.
- Frontend – Creation of search UI.
- Backend – Implementation of ‘ls’ command.
- Chip – Design and implementation of digital circuits
Since these problems are fundamental and educative, we hope it can be a good reference for those who learn in these fields through practical programming.
If you could solve the problems, or if you got interested in PFN, we are looking forward to receiving your applications in the following internship programs.
We are also hiring full-time employees in Tokyo, Japan and San Mateo, California.
Please refer to the job page below.