Recruitment

Recruitment

Yamaha Corporation is seeking talented and motivated R&D engineers from around the world for its internship program.
Interns will be based at Yamaha’s Innovation Center, working closely with researchers and engineers as members of project teams. The program runs for approximately 12 weeks, with travel and accommodation expenses fully covered.This is a unique opportunity to gain hands-on experience and contribute to cutting-edge innovation at Yamaha.

Global Internship

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Research & Development Division

The Summer 2026 internship application period is closed. If you have already submitted your application, you will be notified by the end of December 2025.

Outline (2026 Season)

Term Approximately three months, Summer to Autumn 2026
Division Research & Development Division
Location Hamamatsu/Yokohama, Japan
Application Details will be provided when the application form opens on 29 September 2025.
Requirement Doctoral or master's students in engineering, computer science, mathematics, or related fields.
Condition Paid internship
Benefits Interns will receive a stipend. We also provide:
・ Visa application support
・ Transportation cost assistance
・ Furnished accommodation
Process Application submission followed by an online interview
Due date 21 November, 2025 (The application form will close at 5:00 PM JST on 21 November 2025)
Application of Machine Learning Technique to the Simulation of Wind Instruments

Application of Machine Learning Technique to the Simulation of Wind Instruments

A variety of design elements influence the timbre, intonation, and playability of wind instruments. It is important to physically understand each individual element as well as the inter-relation between them. Additionally, it is essential to remember that wind instruments generate sound through the interaction between the reed and the air column. The combination of simulation and measurements has long been employed in order to physically understand the behavior of wind instruments. However, the simulation of wind instruments inherently requires huge computational cost in order to reproduce fluid dynamics phenomena as well as the interaction with the reed. This internship focuses on predicting the characteristics of wind instruments by combining machine learning and simulation in a fast and efficient manner.

Required:

  • Experience in programming (Python, C/C++, Matlab)
  • Expertise in machine learning

Welcomed:

  • Experience in numerical simulation (especially physics Informed neural networks)
  • Experience in playing wind instruments

Related Technology:

Relationship between the Directivity of Sound Sources and the Spatial Impression of Musical Instruments

Relationship between the Directivity of Sound Sources and the Spatial Impression of Musical Instruments

Musical instruments are characterized not only by their timbre, but also by the way in which they radiate sound spatially. Modern microphone arrays make it possible to measure directivity in detail. However, the manner in which directivity influences human auditory perception is not understood well. Interns will focus on modeling the directivity of musical instruments, extracting perceptually meaningful features from raw measurements, and carrying out psychophysical experiments to determine which aspects of directivity are most strongly linked to perceptual sound quality.

Required:

  • Expertise in array signal processing, spatial acoustics, programming (Python)

Welcomed:

  • Knowledge of psychophysics including experiment design and statistical analysis
  • Knowledge of physics constrained sound field modeling
Development of Low-Latency and Online MIR Methods for Music Understanding

Development of Low-Latency and Online MIR Methods for Music Understanding

We are striving to create new experiences for musical instrument performers through the use of AI for music understanding, such as music transcription and source separation. For interactive uses, it must be an online system with low latency. Recent work in online inference using models like transformers is starting to enable deep learning to be applied to real-time tasks, including music understanding. During this internship, interns will explore a variety of recent deep neural networks (DNNs) for online inference and apply them to music understanding tasks.

Required:

  • Solid expertise in deep learning for music understanding, or for online inference, using frameworks like Pytorch

Welcomed:

  • Experience in creating real-time applications using deep learning
  • Experience in creating real-time audio applications
  • Experience in reducing latency or computation burden of a large deep neural network

Related Technology:

Using Video Data to Analyze Live Music

Using Video Data to Analyze Live Music

This project aims to develop a system that supports efficient and creative music production through a video-centric approach to real-time, detailed scene analysis of live performances. To achieve this, interns will join our Multimodal Sound Optimization R&D Team and research multi-modal live scene analysis. Yamaha is actively researching and developing AI-powered functions for live mixers, to enhance support for PA engineers. Although current systems mainly use audio signals, recent advances in video analysis and Large Language Models promise exciting new possibilities. Interns will analyze video data to extract insights into live performances. We will analyze stage dynamics, audience engagement, and event transitions to deepen our understanding of live music events and contribute to more intelligent mixing assist systems.

Required:

  • Proficiency in programming (Python, C++)
  • Expertise in video analysis technology
  • Knowledge of Large Language Models (LLMs)

Welcomed:

  • Knowledge of music information processing
  • Experience in music production
  • Knowledge of sound engineering
Analyzing Individuality in the Workflows of Mixing Music

Analyzing Individuality in the Workflows of Mixing Music

This project aims to develop a system that supports efficient and creative music production, by researching the structural analysis and modeling of "mixing workflows." Interns on the Mixing Technology R&D Team will analyze operations and sound design patterns, and use machine learning to extract and model key features. Mixing involves the application of audio effects (AFx) to multitrack audio, followed by musical adjustments and mixdown. Mixing engineers construct a sound image that includes AFx chains and audio stems. Although building models that capture the individuality and consistency of each engineer is a challenge, it is key to developing models that enable the construction of personalized mixing models. Interns will explore new possibilities for music production in terms of individual creativity.

Required:

  • Expertise in programming (C/C++, Python)
  • Expertise in machine learning or statistical analysis

Welcomed:

  • Knowledge of mixing process and audio effects
  • Expertise in audio signal processing
Closed

Product Development Division

Spring & Summer 2026 internship application is closed. All applicants will be notified by the end of December 2025.

Outline

Term Approx. 10-12 weeks, January - March, or May - September 2026
Division Core Tech Development, Digital Musical Instruments Development Department
Location Hamamatsu (only 90 minutes from Tokyo/Osaka), or Yokohama, Japan
Application Please submit a cover sheet which clearly designates your target project, along with your résumé/CV and additional materials to back-up your skills & experiences required by each project.
Condition Paid internship
Benefits Travel and commutation expense, housing with bed, washer, kitchenet & wifi, stipend for meal, Japanese visa assistance and language lessons available
Process Documentary screening followed by online interview
Due date November 28th, 2025 (first-come, first-serve policy)
Mixed Reality (MR) App development and content creation

Closed

Mixed Reality (MR) App development and content creation

Core Technology Development Department

Process & Objective

Plan, design, and develop an "Mixed Reality (MR)" experience application that combines Yamaha’s binaural spatial audio technology for XR, named "Sound xR Core", with urban and architectural data from areas such as Minato Mirai, Yokohama. As part of the spatial impression and sound expression design, you will develop signal processing modules, such as filters as needed, and integrate them into the MR application.

SKILLS

  • Knowledge of acoustics (acoustic theory, architectural acoustics, etc.)
  • Knowledge/Experience in C# - Creating digital filters, audio signal processing algorithms, and their programming
  • Knowledge/Experience in creating interactive XR (MR/AR/VR) applications using Unity
                                   WebApp Development for Professional Audio Devices

Closed

App/Cloud Service Development for Professional Audio Devices

Core Technology Development Department

Process & Objective

Define requirements for Apps/Cloud Services managing installation PA systems, Validate requirements by UI prototyping, Decompose requirements into new development elements as Apps/Cloud Services, Document possible requirements

SKILLS

  • Knowledge/Experience in AWS and smartphone App development using OOPL
  • Knowledge/Experience in Prototyping using Adobe and/or Figma
  • Knowledge of UX/UI Design, User-Centered Design (UCD)
  • Experience in shared development project as a Product Manager or UX Designer
Quality Tests for Professional Audio Products

Occupied

Development of PC Software for Digital Musical Instrument Content Creation
(Content: MIDI Song, Style, Voice Parameter, etc)

Digital Musical Instuments Development Department

Process & Objective

o Contribute to the development of PC software tools for digital musical instruments content creation
o Design and implement user interfaces optimized for music content workflows

SKILLS

  • Required: Fundamental knowledge of Human-Computer Interaction (HCI) principles or UI/UX design, Skills in statically typed programming language (e.g., C++, C#, Java, etc.), Experience with musical instruments, music production, or using DAWs.
  • Desirable: Basic understanding of MIDI protocol and digital audio concepts, Software development skills with UI development frameworks (Qt, Flutter, JUCE, etc.), or cross-platform development (Windows/macOS), skills using version control systems (e.g., Git), Experience using design tools such as Figma or Adobe XD, Experience collaborating on projects using version control systems (e.g., Git)
Quality Tests for Professional Audio Products

Occupied

Prototyping a Music Learning Support App for Beginners

Digital Musical Instuments Development Department

Process & Objective

o Prototype a mobile learning app that helps beginner musicians improve their instrument performance step by step.
o Research and design user-friendly UI/UX, implement key features, and evaluate how the app supports continuous learning.

SKILLS

  • Required: Basic knowledge of UX/UI design, Skills in iOS and/or Android App development, Interest in playing musical instruments, Open-minded communication
  • Desirable: ・Knowledge of playing musical instruments or music production, Specialized knowledge in UI/UX design, Interest in education or learning sciences, Basic knowledge of MIDI
    ・Cross-platform development skills (e.g., Flutter, ReactNative)
    ・Experience in team-based software development, improving or optimizing UI/UX
    ・Interest in Japanese culture
CLOSED

Post Doctoral Position

The application period for Post Doctral Position has been closed.
Please await further announcements regarding our next call for applications.

                                                                                                           
Position Researcher for Audio Signal Processing and Music Informatics
Location Hamamatsu/Yokohama, Japan
Description
  • Develop audio signal processing and music informatics algorithms to support new features for digital mixing consoles, digital functions of musical instruments, and tone generators
  • Productize prototypically the features for Yamaha's musical and audio devices including real-time systems
  • Demonstrate creative problem-solving
  • Work closely with other team members and multi-functional partners through in-person or online communication
  • Participate in academic conferences to stay abreast of state-of-the-art algorithms, and research advances in the audio signal processing and machine learning research fields
Qualifications
  • Ph.D. in CS or EE
  • industry experience preferred
  • 5+ years experience in audio signal processing or music informatics development
  • Expertise in real-time audio signal or music informatics processing
  • Theoretical understanding of statistical signal processing and machine learning
  • Familiarity with common software engineering practices and version control
  • Proficiency in C, C++, MATLAB, and Python
  • Critical listening skills
Due Date 15 September, 2024 (Messages via the contact form must be received no later than 11:59 pm on 15 September 2024, SST (UTC -11:00).)
How to Apply Please fill in the required fields in the application form as well as enter the information below when applying.
  • Enter “Postdoctoral Position” in the Subject field.
  • Select “Internship” for the Inquiry Subcategory.
  • For the Questions/Comments field, enter a brief summary of your academic and professional background as well as your current affiliation.
  • Due to system limitations, you cannot attach a CV. After we receive your application, we will inquire with you by e-mail about information required for applicant screening, such as your CV.
Closed