Positive Grid is devoted to creating cutting-edge technologies to revolutionize the world's music production. We are seeking a Senior Music Technology Research Engineer with a strong theoretical foundation and proven industry experience to join our DSP Team. This role will focus on advancing our technical capabilities through research in physical modeling of guitar amplifiers and effects, audio signal processing theory, and the integration of AI-driven methodologies into our development process.
【Typical Accountabilities】
-Lead research initiatives in physical modeling of guitar amplifiers and effects, with emphasis on theoretical foundations and systematic validation
-Develop theory-driven architectures and algorithms for audio processing systems with rigorous mathematical validation
-Design and implement filter systems with thorough understanding of phase response, distortion characteristics, and mathematical underpinnings
-Create and optimize real-time audio processing algorithms based on physical models rather than subjective tuning
-Establish comprehensive testing methodologies with objective metrics for audio processing quality validation
-Document technical decisions, validation processes, and implementation strategies with clear theoretical justifications
-Stay current with academic research in audio DSP and translate theoretical advancements into practical implementations
-Collaborate with international engineering teams to integrate research findings into production systems
-Mentor team members on theory-driven development methodologies and validation techniques
-Drive technical excellence and innovation in music technology development
【Technical Focus Areas】
-Physical modeling of guitar amplifiers and effects with emphasis on filter design and nonlinear systems
-Time and frequency domain analysis of audio systems with rigorous mathematical foundations
-Audio signal processing research with focus on real-time implementation
-Objective validation methodologies for audio processing quality assessment
-Music information retrieval and computational audio analysis
-AI-enhanced audio processing and machine learning applications in music technology
【People Management Responsibility】
-This role does not have direct management responsibilities but will provide technical leadership and mentoring.
【Essential】
-PhD in Electrical Engineering, Computer Science, Physics, Applied Mathematics, or a related field with a focus on audio signal processing
(or Master's degree with 5+ years of relevant industry experience)
-3–5 years of industry experience in audio technology, signal processing, or related fields
-Strong theoretical foundation in signal processing, including:
-Digital filter design principles and mathematical modeling
-Nonlinear systems analysis and implementation
-Time and frequency domain transformation techniques
-Physical modeling of analog circuits and audio systems
-Demonstrable research experience in audio signal processing, music technology, or physical modeling
-Proficiency in at least two of the following: C++, MATLAB, Python, or similar languages for algorithm development
-Understanding of guitar amplifier circuits, effects, and tone characteristics
-Ability to design and implement systematic validation processes with objective metrics
-Strong communication skills in explaining complex technical concepts and writing documentation
-Critical thinking skills with the ability to challenge established methodologies
-Proven track record of delivering production-quality audio processing solutions
【Desirable】
-Publications in audio signal processing, physical modeling, or music technology
-Experience implementing real-time audio processing algorithms in production environments
-Understanding of machine learning principles applied to audio processing
-Familiarity with guitar amp simulation plugins (e.g., Neural DSP, ToneX, Helix, BIAS, etc.)
-Experience with Digital Audio Workstations (DAWs) and audio plugin development
-Guitar playing ability or music theory knowledge
-Experience working in collaborative software development environments
-Knowledge of audio industry standards and best practices
-Experience integrating with audio hardware or embedded systems