ConFlow Power Group
CUDA Engineer
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Company Description
ConFlow Power Group develops an adaptable suite of complementary technologies, combining proprietary innovations, licensed solutions, and joint venture projects. The company’s initial flagship product is an advanced smart lighting solution, redefining how street lighting is designed and managed. By reimagining street lights from a necessary cost into a revenue-generating asset, ConFlow Power Group focuses on both innovation and commercial value. Team members collaborate on cutting-edge technology that has tangible impact on urban infrastructure and smart city development.
Role Description
The CUDA Engineer role is a contract, hybrid position based in the United Kingdom, with flexibility for partial work from home. This role involves designing, implementing, and optimizing GPU-accelerated algorithms and applications using NVIDIA CUDA for ConFlow Power Group’s smart technology solutions. Day-to-day tasks include profiling and tuning performance-critical code, integrating GPU components into existing software architectures, and collaborating with cross-functional teams to translate product requirements into efficient parallel implementations. The CUDA Engineer will also contribute to testing, debugging, and documenting GPU-related modules, ensuring reliability, scalability, and maintainability of the codebase. Participation in technical reviews, knowledge sharing, and continuous improvement of development practices is expected.
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Qualifications
- Strong proficiency in CUDA programming and parallel computing, including experience with GPU performance optimization and memory management.
- Solid skills in C/C++ software development, debugging, and code profiling within modern development environments and toolchains.
- Understanding of algorithms, data structures, and numerical methods relevant to high-performance and scientific or engineering computations.
- Experience integrating GPU-accelerated components into larger systems, including familiarity with APIs, libraries, and scripting for automation.
- Knowledge of software engineering best practices such as version control (e.g., Git), unit testing, and continuous integration.
- Ability to collaborate in hybrid teams, communicate complex technical concepts clearly, and work independently with minimal supervision.
- Bachelor’s degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience.
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Preferred:
- Experience with smart devices, embedded systems, edge computing, or IoT solutions
- Familiarity with other GPU frameworks (e.g., OpenCL) is an advantage
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