Call for Applications: PFN 2025 Summer Internship in Japan
2025.03.26
At Preferred Networks (PFN), we are seeking passionate students to join our summer internship program. We welcome applicants from diverse academic backgrounds in computer science—not limited to those specializing in machine learning.
Index
- About PFN Internship
- Internship Courses and Themes
- Qualifications
- How To Apply
- Screening Process
- Salary and Benefits
About PFN Internship
At PFN, our mission of "making the real world computable" drives us to rapidly translate cutting-edge technologies into practical applications, thereby delivering new value to society. We are devoted to creating competitive technologies and promoting their practical usage in society by vertically integrating the AI technology value chain within our company, including AI chips, computing platforms, foundation models, solutions, and products. Currently, these technologies are being deployed across various industrial sectors, such as manufacturing, materials, pharmaceuticals, energy, healthcare, retail, entertainment, and education.
In the rapidly evolving fields of machine learning and AI, we champion a culture of humble learning and continuous growth. Embracing the challenge of fearlessly venturing into new and unfamiliar domains is at the heart of PFN Values. Our internship offers a prime opportunity for students to experience firsthand our research-and-development efforts that truly embody these values. If you are keen on cutting-edge R&D and the technologies that empower it, eager to apply advanced machine-learning technologies to real-world problems, and ready to learn and explore new fields alongside our team, we warmly welcome your application.
PFN values the diversity of our team and ensures a safe and secure workplace for everyone. We eagerly look forward to receiving applications from candidates of all races, genders, and nationalities.
Qualities We Look For in Candidates
At PFN, we extend a warm welcome to students who have the qualities listed below. If there is an episode in your life that echoes these traits, we strongly encourage you to include it in your application or resume.
- Have strong motivation to solve problems through technology, create user value, and embrace the challenge of forging novel value
- Embrace an open mindset to delving into multiple domains, continually expanding skills and knowledge base
- Possess basic communication skills, capable of fostering positive relationships with individuals from various backgrounds, contributing proactively in a team environment
- Possess a basic understanding of computer science coupled with an eagerness to explore the frontiers of technologies such as deep learning and computing infrastructure, and have gained relevant experiences, such as a university major, self-learning via online courses, part-time jobs, or internships.
Contact Us
Have questions about our internship program? Feel free to ask them via our Inquiry Form.
Whether you have questions about the selection process, specific themes, the work environment at PFN or any other aspects of the internship or about our company, please don't hesitate to contact us.
Messages From Past Interns and PFN Employees
Participation Year: 2024
Academic Year When Interned: 1st-year Master's Student
Internship Theme：Lightweight Inference of Large Language Models
About Me
Hello, I am Honoka Anada, enrolled as a first-year master's student in the Department of Computer Science at the University of Tokyo's Graduate School of Information Science and Technology. While in graduate school, I am engaged in the research of building reliable federated learning systems, including mechanisms for evaluating participant contributions in federated learning.
My Internship Project
During the internship, I undertook a project under the theme of "Lightweight Inference of Large Language Models." The project involved fine-tuning a relatively small LLM by knowledge distillation from a larger LLM.
My Motivation for Joining the Internship Program
I have always been aware of PFN, identifying it as a gathering place for highly skilled professionals with a passion for technology. My primary motivation for applying for this internship is the enticing opportunity to engage in profound technical discussions within such a stimulating learning environment.
Besides, PFN engages in comprehensive research and development in deep learning, from the foundation of hardware level, as demonstrated by their work on MN-Core. This aspect profoundly resonated with me due to my varied interests, ranging from machine learning to hardware and system development.
Key Learnings From My Internship Experience
During my internship, I had the opportunity to explore the development of LLMs, a field distinct from my research on machine learning at university. Despite being a novice in the field of LLMs, I found the contrast in techniques and training methodologies used was quite striking. The scale and approach also vastly differ from small-scale machine learning. Witnessing the R&D of LLMs firsthand was a unique learning experience that I am sure to utilize in my future projects.
Moreover, the internship offered me the opportunity to network with engineers from many different teams, including infrastructure, compilers for deep learning, and drug discovery. Being exposed to the forefront of technology within these fields was an immensely stimulating experience, reminding me of the broad and deep technological landscape that exists.
Who Should Consider the PFN Internship
Interning at a company renowned for pushing the boundaries of technology can prove to be a profoundly valuable experience. It allows you to expand your horizons beyond the usual realm of university research, offering a fresh and varied perspective. I would unhesitatingly recommend this internship to anyone eager to enhance their expertise in their current field of study, as well as those looking to venture into a new domain.
Participation Year: 2022 (Joined PFN as a new graduate in 2024)
Academic Year When Interned: 1st-year Master's Student
Internship Theme：Development of MN-Core Compiler and Libraries
About Me
Hello, I am Yotaro Nada and started my career at PFN as a fresh graduate in 2024. At PFN, I am primarily involved in the RTL implementation of MN-Core, focusing specifically on memory-related implementation. During the implementation process, my role requires me to secure the necessary broad memory bandwidth for deep learning and HPC applications, while also keeping the circuit area to its minimum possible size. This requires short cording-like techniques such as utilising a single buffer for various purposes and amending the pipeline structure, making my job reminiscent of solving an interesting puzzle.
As a student, I conducted research on the microarchitecture of processors in the Department of Electronic Information Engineering at the University of Tokyo's Graduate School of Information Science and Technology. There, I proposed a slightly non-conventional C++ compiler implementation for instruction sets and a lightweight out-of-order execution mechanism designed to operate on in-order cores.
My Internship Project
During my internship, I worked on the development of a feature that automatically produces optimization suggestions for MN-Core assembly. As MN-Core does not have mechanisms like cache memory or conditional branching, almost all runtime events can be anticipated during the compiling stage. Leveraging this information, I developed a system capable of automatically identifying potential areas of optimization within the input assembly.
My Motivation for Joining PFN's Internship Program
I was in a phase of my life where I was unsure about my career path but possessed a vague aspiration to work on low-level software. It was during this period of uncertainty that I came across the PFN internship recruitment description. Having never been exposed to MN-Core or even a GPU before, I had my share of doubts regarding my acceptance into the internship program, but I decided to apply anyway.
Key Learnings From My Internship Experience
The most valuable takeaway from my internship was the hands-on exposure to the world of commercial processor development, working directly with the MN-Core compiler and chip. I had the chance to experiment with the compiler and it was astonishing to see how all the essential tools, like register allocation and instruction scheduling, had been ingeniously implemented from scratch.
I believe there are many among you who, like me, have attempted to craft your own simple compilers or cores from scratch and have derived immense pleasure from the process. The internship provided a valuable experience in understanding that there are professional avenues where one's passion for building compilers or cores can transform into a product or even carve a career out of it.
Who Should Consider the PFN Internship
The PFN internship is particularly recommended for individuals with a keen interest in low-level software but might feel uncertain or have concerns about pursuing a career in this field or for those who have no concrete idea of what this line of work entails. The program is designed to be approachable even for those who are unfamiliar with accelerators like MN-Core. With detailed mentoring ranging from hardware specifications to compilers, you can gain firsthand experience of the chip and compiler development process without any struggles.
Moreover, the program also offers the opportunity to glimpse into PFN's comprehensive approach to technology, wherein various elements, right from chips and their runtime to cluster systems, are developed in-house. For enthusiasts of low-level software, it would be a thoroughly gratifying experience.
Blog article about Yotaro Nada's internship project: Automatic Generation of Optimization Hints for MN-Core (in Japanese)
Participation Year: 2024
Academic Year When Interned: 1st-year Master's Student
Internship Theme：Machine Learning Platform Engineer Work Experience (Kubernetes/Infrastructure)
About me
Hello, I am Soichiro Ueda, currently pursuing my first year of Master's degree at Kyoto University's Graduate School of Informatics. My academic focus is on cloud computing and system software, with an emphasis on a specific technology known as unikernel. Outside of my academic studies, I actively participate in building and operating Kubernetes clusters, both personally and as part of student teams.
My Motivation for Joining PFN's Internship Program
My decision to apply for PFN's internship program stemmed from my interest in developing large-scale on-premise infrastructure. The fact that PFN is developing a large-scale GPU cluster based on Kubernetes piqued my curiosity. Coupled with my own experience in operating Kubernetes, I was confident that this program would provide the environment to utilize and further refine my skills in Kubernetes-related development.
A Typical Day as a PFN Intern
A day as a PFN intern for me began with a meeting with my mentor after getting to the office at around 9:00 a.m. Later around noon, I would have lunch with the team and other interns. My main development task was to implement a new feature, namely resource synchronization, into an OSS called Kubernetes Scheduler Simulator and make a contribution to its upstream. During the meetings, we discussed both implementation specifics and how to interact with maintainers.
Key Learnings From My Internship Experience
Through the project of incorporating a feature into a Kubernetes subproject, I learned effective communication skills within OSS environments. The process entailed engaging in active discussions with community members about the feature I was implementing to ensure we all shared the same understanding. Furthermore, it also provided me the opportunity to read through the internal Kubernetes codebase, allowing me to gain an insight into the internal implementation of Kubernetes.
Who Should Consider the PFN Internship
This internship is a fantastic opportunity to immerse oneself in the advanced development of machine learning infrastructure that utilizes Kubernetes. PFN is known for its unique projects, like the addition of inhouse extensions to the Kubernetes scheduler, making this internship highly recommendable for those seeking a deeper development experience. If this piques your interest, I suggest exploring PFN's technical blog to see if any project aligns with your interests.
Blog article about Soichiro Ueda's internship project: Development of Resource Synchronizer for Kubernetes Scheduler Simulator (in Japanese)
Participation Year: 2024
Academic Year When Interned: 2nd-year Doctoral Student
Internship Theme：Applied Research and Development of Machine Learning and Atomic Simulation on Materials
About Me
Hello, my name is Kentaro Hino, and I am a second-year doctoral student at Kyoto University's Graduate School of Science. At university, I am engaged in the development and implementation of computational theory within the field of quantum chemical computation. More specifically, it involves estimating physical properties by numerically solving the Schrödinger equation, which essentially dictates the physics of molecules. One particular area which I find interesting and dedicate much of my research to is tensor networks. This involves a technique for effectively converting high-dimensional data into low-dimensional data using tensor decomposition.
My Internship Project
During my internship, I worked on the project of molecular structure generation using a diffusion model under the theme, "Applied Research and Development of Machine Learning and Atomic Simulation on Materials". An interesting aspect of this model was its training process: Rather than learning to reconstruct noise, it is trained to learn the governing equations of stochastic processes in which noise is diffused. As a result, it generates molecular structures not from "the distribution of molecular structures stored in a database", but from "the distribution of molecular structures as per physical equations." My internship program began with refreshing my knowledge of statistical mechanics and stochastic processes used in physics. The middle phase involved building a predictive model using Transformer and demonstrating its generation. The final part of my internship involved examining difficulties facing the model's training, and I was able to find a guiding principle.
My Motivation for Joining PFN's Internship Program
Matlantis is a product developed by PFN and is widely recognized in my field of theoretical chemistry, and naturally, I was aware of it quite early on. However, my decision to participate in the internship program was influenced by several factors. Firstly, while I was presenting a poster at a study group for young researchers, a PFN employee approached and invited me to consider the internship program. Secondly, a respected acquaintance of mine, a former PFN intern, spoke fervently about his positive experiences during that period. Further, the recent advancements and the fascinating work happening around molecular generative models hold a particular appeal for me, and I have a strong interest in this area. However, as a physical chemistry major who doesn't specialize in machine learning, pursuing this field on my own seemed quite challenging. Therefore, joining an internship program that could provide practical exposure to the latest knowledge in this field seemed like the ideal avenue for my learning ambitions.
How I Spent My Internship Days
Because I live in Kyoto, I made the daily commute from my parents' home in the Kanto region to work in the office during my internship, instead of taking advantage of a rent subsidy to stay in a weekly apartment close to the office. Thankfully, the PFN office's convenient location, being directly connected to a nearby subway station, significantly reduced the commute burden. For the initial part of my internship, which was more learning than implementation, I spent my spare time delving into technical books and articles. My daily schedule typically ran from 9:00 to 18:00 – a comfortable rhythm that mirrored my university research schedule. What I found particularly enriching were interactions with PFN employees during lunch breaks and team meetings where I learned about technical insights and various development styles. While some interns juggled their university research with internship, I chose to focus solely on my internship as I had reached a good stopping point in my academic research. Nevertheless, I appreciated the flexibility the internship program offered, allowing me to alter my work schedule for conference presentations.
Key Learnings From My Internship Experience
In all honesty, this was my first encounter with diffusion models, transformer models, and even implementing from scratch with PyTorch. However, through a process of trial and error, I was able to master them to a degree that I can apply them in my research, empowering me to critically examine papers on computational chemistry using neural networks. Another realization that took me by surprise was the depth of expertise among the researchers and engineers involved in developing Matlantis' service. Initially, I held the impression that PFN was purely a machine learning-focused company, but I discovered a solid foundation of many computational chemistry experts actively contributing to its growth. Having the opportunity to witness such an environment firsthand was a precious experience.
Who Should Consider the PFN Internship
I highly recommend this internship to individuals specializing in biology, physics, or chemistry who have developed an interest in machine learning after reading textbooks or study-aid books about it but find it challenging to apply in their research work. For me, molecular system calculations was the only similarity between my university research and my internship project. Still, after two months of goal-driven trials and errors, I can confidently say that one can attain results that far exceed initial expectations.
Blog article about Kentaro Hino's internship project: Molecular structure generation by diffusion Model for Finite Temperature Systems (in Japanese)
Participation Year: 2024
Academic Year When Interned: 1st-year Master's Student
Internship Theme：Reconstruction, Editing, and Generation of 3D Models and Free-Viewpoint Videos
About Me
Hello, I am Yi-ming Liang, a first-year master's student enrolled in the Department of Computer Science and Engineering at Waseda University's Graduate School of Fundamental Science and Engineering. My main interest lies in the field of 3D computer vision and I am engaging in research on 3D model reconstruction at my university. My study focuses on simplifying the creation of high-quality 3D models with an aim to make 3D model-based content more readily accessible to all.
My Internship Project
During my time as an intern, I worked on a project to reconstruct a dynamic 3D Gaussian Splatting (3DGS) model from a single video clip. Existing methods typically necessitate the synchronization of multiple cameras and capturing videos from different angles. Attempting this with just a single video often results in a failed reconstruction, as the shapes can become corrupted when viewed from a new viewpoint. To address this issue, I proposed a method to prevent shape collapse by introducing a hierarchical structure to represent temporal changes within the 3DGS model. The work I conducted during my internship got accepted for CVPR 2025.
My Motivation for Joining PFN's Internship Program
I already had an interest in PFN 3D/4D Scan service prior to my internship. When I learned that one of the internship projects was related to 3D model reconstruction, it aligned perfectly with my research and prompted me to apply. I saw the prospect of working alongside PFN employees on R&D objectives as a valuable opportunity to further develop my technical competencies.
Key Learnings From My Internship Experience
Through daily discussions with my mentor, I learned about conducting research effectively. To produce research results within a short timeline, I aimed to implement and validate ideas as quickly as they occurred to me, which greatly improved my implementation skills. Moreover, the poster session for the final presentation not only provided me a great practice venue to present my work but also allowed me to receive valuable feedback from other interns and PFN employees, which helped enrich my research. The presentations by other interns were also a valuable source of learning and inspiration. Additionally, participating in events such as PFN Day gave me a comprehensive understanding of PFN's business operations and company culture.
Who Should Consider the PFN Internship
PFN internship is not just about technical growth but it offers numerous opportunities to interact with PFN employees and other interns. This helps to expand your horizons and keeps you stimulated, fueling personal and intellectual growth each day. So, if any intern theme catches your interest, I strongly recommend giving it a shot.
Internship Courses and Themes
This year, PFN's internship program offers two different courses, each with its own set of research and development themes. As an intern, you will have the privilege of being mentored by our experts across diverse domains including foundation models, computing infrastructure, computer vision, life science, and product/service development. This program, regardless of any course and theme, not only allows you to engage in research and development firsthand but also provides opportunities for valuable interactions with PFN's management team and our full-time professionals.
Once we receive your application, you will receive a notification about an assignment for screening purposes. Please indicate your preferred course and theme when you submit this assignment. The actual theme and exact scope of your internship work will then be determined through discussions with PFN members during the selection phase.
Click here for the full list of internship themes (PDF)
Please note, any intellectual property generated during your internship will belong to PFN. We ask that you refrain from incorporating research themes from your affiliated institution to avoid conflicts. Additionally, we encourage the publication of your internship work through OSS contributions, research papers, or blog posts on the PFN Research & Development Blog, provided there are no confidentiality or IP rights issues.
10-Day Short-Term Development Course
This is a short-term internship program where you will join one of PFN's project teams to engage in hands-on research and development activities.Your attendance is mandatory, in principle, for all days within the chosen duration.
- Period: Two sessions are available, each spanning 10 business days.
- Monday, August 18 through Friday, August 29, 2025
- Friday, September 5 through Friday, September 19, 2025
7-Week R&D Course
You will spend seven weeks deeply engaged in in-depth discussion and R&D work, mentored by PFN's engineers/researchers, aiming to achieve meaningful R&D results.
- Period: Thursday, August 7 through Friday, September 26, 2025
- In principle, the internship period must be within your university's official summer break. Start and end dates are flexible, subject to your academic schedules and other considerations.
- Absences for lab activities, academic conference attendance, or personal reasons such as returning to your hometown will be flexibly accommodated.
The themes offered in our 7-week R&D course are categorized as either a "project internship" or a "research internship" based on the nature of the work involved. We have compiled a list of achievements from last year below for your reference. Please use this information to help guide your theme selection.
- Project Internship
- Through our Project Internship, you will engage in hands-on project work with a focus on practical problem-solving, the research and development of core technologies, and the development of products and services.
- Example achievements in the past:
- OpenTelemetry integration for Matlantis
- Development of a Testing Tool for Kubernetes Validating Admission Policy (Japanese Article)
- Realizing Log Alert in a Kubernetes Environment (Japanese Article)
- Investigation and Verification of Kubernetes Mutating Admission Policy (Japanese Article)
- Development of Resource Synchronization Function for Kubernetes Scheduler Simulator (Japanese Article)
- Design and Construction of Log Infrastructure in PFCP (Japanese Article)
- Implementation of Profile Function for PFIO (Japanese Article)
- Development of a Tool to Measure Internet Traffic Volume per Pod Using eBPF (Japanese Article)
- Improving the Estimation Accuracy of DRAM-SRAM Data Transfer Time in MN-Core 2 (Japanese Article)
- Support for CUDA Graph Conditional Nodes in CuPy (Japanese Article)
- Consideration on Lightweighting of Speech Recognition Model Incorporating PLaMo (Japanese Article)
- Development of a Text Embedding Model Based on PLaMo (Japanese Article)
- Analysis and Improvement of LLM Agent Capabilities in PLaMo (Japanese Article)
- OpenTelemetry integration for Matlantis
- Research Internship
- Our Research Internship invites you to engage in pioneering and ambitious research projects with the goal of publication in top-level international conferences.
- Example achievements in the past:
- meta-fuse-csi-plugin: A CSI plugin for All FUSE implementations
- Unified evaluation of deep option pricing methods
- Consideration on Improving Accuracy of Mathematical Reasoning Tasks Using Synthetic Datasets in LLM (Japanese Article)
- Dataset Augmentation for Classification Tasks Using LLM (Japanese Article)
- Generation of Financial Time Series Using Conditional Diffusion Models (Japanese Article)
- Consideration of Few-Shot Product Image Classification Method Using Diffusion Features (Japanese Article)
- Development of 4D Gaussian Splatting Web Viewer and Motion Sequence Function (Japanese Article)
- Blowin' in the Wild: Development of 4D Gaussian Splatting from Disparately Captured Images (Japanese Article)
- Construction of Neural Network Potential Considering Spin Degrees of Freedom and Dataset Creation Using cDFT (Japanese Article)
- Application of LightPFP to Enzyme Reactions (Japanese Article)
- Molecular Structure Generation Using Diffusion Models for Finite Temperature Systems (Japanese Article)
- meta-fuse-csi-plugin: A CSI plugin for All FUSE implementations
- Our Research Internship invites you to engage in pioneering and ambitious research projects with the goal of publication in top-level international conferences.
Qualifications
To be eligible for our internship program, applicants must satisfy the following prerequisites:
- Applicants must be students aged 18 or older, and not employed as a full-time employee elsewhere as of the date the internship begins (Exceptions may be made for individuals with different statuses on a case-by-case basis).
- Language Proficiency: Fluency in either Japanese or English is required, with the ability to engage in proactive communication.
- Office Attendance: Applicants must be able to work at our Otemachi office near Tokyo Station on required weekdays. Accommodation support is available for those who live far away (For details, see the Support for Participants from Distant Areas section)
- Legal Eligibility: Applicants must have the legal right to undertake internship or part-time work in Japan (e.g., Japanese nationality, permanent residency, student visa).
- Equipment: Applicants must have a personal laptop that can be used for development tasks during the internship.
Additional consideration will be given to applicants with knowledge and experience in areas related to our Internship Courses and Themes. For details, please refer to the specific theme descriptions provided.
We welcome applications from those new to full-scale development and also encourage those who have applied in the previous years to consider reapplying. However, previous participants in our past internship programs are not eligible to apply again.
Should you require university credit for this internship, advance communication with us is required. Please note, however, that we may not accommodate requests involving complex administrative procedures.
For International Students
If you are an international student studying at university in Japan under a student visa, you must apply for and obtain the "Permission to Engage in Activity other than that Permitted under the Status of Residence: 資格外活動許可 in Japanese" prior to commencing your internship. Upon signing the contract of employment, you will need to submit a copy of your residence card.
Development Environment
For the duration of the internship, participants must use their own laptop PCs for all development-related tasks. Please note that the company will not provide laptops for intern use.
Important Notes for Your Laptop:
- The company will not provide laptops or financial assistance for purchasing one. Additionally, laptops loaned by your university or organization cannot be used for internship purposes.
- The laptop must be your own or belong to your family member.
- You may be asked to install specific software as required by your internship project.
Your laptop doesn't need to have high-end specifications; it should be just capable enough to handle typical university tasks like assignments and classes. Below, we provide recommended PC specifications to guide your preparation for the internship:
- OS：Windows 11 Pro (Intel) or macOS 15 is recommended
- Otherwise, use an OS version currently supported by the manufacturer
- If your laptop runs on Windows 11 Home, you will need to upgrade to Windows 11 Pro after receiving an employment offer and before the internship begins. We will subsidize upgrade costs for those who qualify.
- Please note that laptops with Windows on ARM are not suitable for this internship as some software may not function properly with this OS.
- If you prefer Linux or other OS, please mention this in your application for further discussion on suitability during the selection process
- Network: Wireless LAN capability
- The device should be capable of handling online meetings and web browsing without difficulty.
- It is not necessary for your PC to support highly computational or data-intensive tasks like machine learning model training.
How to Apply
- Click this Application Form to apply.
- ※You need to log in with your Google account to access the application form.
- ※Personal information entered in the application form will be used for the purpose of intern selection and recruitment activities.
Application Deadline
- 23:59 on Sunday, April 20, 2025 (Japan time, no application will be accepted after the deadline)
Important Notes Upon Applying
- The file format of your resume must be PDF only. Please submit it via the application form.
- We will use the e-mail address you enter in the application form as your ID for the selection process. Please use the same email address when you submit assignments or send inquiries during the screening period.
Tips for Writing Your Resume
- We highly recommend reading the application form before drawing up your resume, as it requests specific information we would like included in your resume. If the information is already covered in your resume, feel free to skip relevant fields in the application form.
- Your resume will be used to assess if your profile aligns with the Qualities We Look For in Candidates. Be as specific as possible in your resume so that we have all the information we need to be able to evaluate your abilities and experience.
- Please describe your award history, research presentations, and coding experience as comprehensively as possible. Even if you find your prior work unremarkable, the information may be valuable in the evaluation process.
- There's no need to write a motivation specific to your choice of theme within your resume. You'll be asked to provide this along with your preferred theme when you submit assignments later in the process.
Screening Process
Assignment assessment (coding test & thematic assignment) → Online interview → Final result announcement
- 23:59 on Sunday, April 20 : Application deadline
- Friday, April 25 : PFN sends assignments to applicants
- 23:59 on Tuesday, May 6 : Deadline for submission of assignments
- Mid-May to late June : Online interview
- Monday, June 30 : Final result announcement
Salary and Benefits
Hourly Wage
- 2,500 yen per hour for technical college, university, and graduate school students
Working hours
- Eight hours in principle. Five days a week excluding Saturdays, Sundays, and public holidays
Workplace
PFN Office is located in Otemachi Bldg., 1-6-1, Otemachi, Chiyoda-ku, Tokyo, Japan 100-0004
You will work in a hybrid style of both working in-office and from home. We do not offer a fully remote internship. Depending on the specific requirements of your chosen course or theme, in-office attendance might be necessary for the entire duration of your internship. Full details about your work location requirements will be shared before the internship begins.
For those days you work in our office, PFN will cover the commute expenses between your home/temporary lodging and our office via company-approved routes.
Support for Participants from Distant Areas
For interns joining from distant locations, PFN will provide financial assistance to cover both travel and lodging expenses during the internship program.
- Travel cost: If your participation in the internship requires long-distance travel, such as by plane or Shinkansen, PFN will cover the expenses for one round trip between the Tokyo area and your home location to facilitate your relocation.
- Accommodation support: During your internship, holidays included, PFN will provide a daily allowance intended to cover the costs of securing accommodation within a reasonable commuting distance to our office.
- You need to secure a place to stay by yourself. Reasonable weekly rental apartments ranging from 100,000 to 150,000 yen a month are available within a commuting distance to the PFN office.
- Please note that the accommodation allowance is subject to taxation.
- 10-Day Short-Term Development Course：6,500 yen per day
- 7-Week R&D Course：5,500 yen per day
Financial assistance for travel and lodging is offered to interns who live in areas outside the following prefectures as of the internship outset:
- Tokyo, Chiba, Kanagawa, Saitama, Ibaraki, Tochigi, and Gunma
Employment Type
Fixed-term employment
Depending on your assigned project, there is a possibility that your placement could be with our subsidiary, Preferred Elements, Inc. (PFE) *Working conditions at PFE are the same as those at PFN.
