Role Summary
Acoustofab is seeking a Research Software Engineer – Real-Time GPU Systems to help develop advanced real-time computational and control systems for next-generation acoustic technologies.
This role focuses on high-performance GPU computing, real-time signal processing, simulation, and hardware/software integration within an experimental R&D environment. The successful candidate will work closely with researchers and hardware engineers to build scalable compute pipelines, optimise real-time control systems, and support the development of novel physical interaction technologies.
Success in this role means contributing to the performance, reliability, and scalability of Acoustofab’s computational platform, including solver optimisation, low-latency system design, and experimental platform development.
The position sits within Acoustofab’s R&D division and contributes directly to the company’s core technology development efforts.
Responsibilities
* Develop and optimise GPU-accelerated real-time compute systems using OpenCL and C++
* Improve performance, scalability, and reliability across low-latency control pipelines
* Build internal tools for simulation, debugging, profiling, and visualisation
* Integrate software with FPGA-controlled and sensor-driven hardware platforms
* Support experimental testing, system characterisation, and prototype development
* Collaborate closely with researchers and hardware engineers on next-generation acoustic systems
Required Skills & Experience
* Strong C++ programming skills
* Strong experience with OpenCL and GPU compute programming
* Experience developing high-performance parallel compute systems
* Understanding of low-latency or real-time software architectures
* Strong mathematical and analytical problem-solving ability
* Comfortable working with experimental hardware/software systems
* Experience debugging and optimising performance-critical systems
Desirable Skills & Experience
* Experience with CUDA, Vulkan Compute, OpenMP, or related compute frameworks
* Experience with DSP, simulation systems, or scientific computing
* Familiarity with FPGA or embedded hardware workflows
* Experience with graphics pipelines or scientific visualisation
* Experience working in research or experimental R&D environments
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