Senior GPU / CUDA Software Engineer
Plaats
netherlandsNederland
Nederland
Contract
Vooltijds, Onbepaalde duurDatum gepubliceerd
2026-09-30Online tot
2026-11-29EUR 15.00 HOUR
Senior GPU / CUDA Software Engineer
Are you an experienced engineer with strong expertise in
GPU programming
and
CUDA
optimization? Do you enjoy working on performance-critical software where mathematics, algorithms, and hardware come together? At TMC, we are looking for a
Senior GPU / CUDA Software Engineer
to work on advanced high-tech applications where processing speed, scalability, and reliability are essential. What will you do?
In this role, you will design, develop, and optimize high-performance C++ and CUDA software for GPU-accelerated applications. You will work on computationally intensive algorithms in areas such as signal processing, image processing, numerical modelling, and AI, translating them into efficient GPU implementations. Your responsibilities will include:
Developing and optimizing high-performance C++ and CUDA software Designing and improving CUDA kernels for maximum execution efficiency Profiling CPU and GPU workloads to identify performance bottlenecks Optimizing memory usage, bandwidth, synchronization, and CPU-GPU data transfers Improving latency, throughput, scalability, and overall resource utilization Applying parallelization, vectorization, computation reuse, and kernel fusion techniques Maintaining numerical accuracy and output quality while improving performance Working closely with FPGA, electronics, firmware, systems, algorithm, and AI engineers Contributing to hardware-software partitioning and complete system architectures What do we expect from you?
A Master's degree or PhD in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, Physics, Biomedical Engineering, or a related technical field Strong professional experience with C++ Deep hands-on experience with CUDA and GPU programming Strong knowledge of CUDA performance optimization, including: memory hierarchy memory bandwidth occupancy CUDA streams CPU-GPU data transfer Experience with profiling and performance-analysis tools Strong understanding of object-oriented software design and maintainable software architecture A solid mathematical foundation Experience in one or more of the following areas is highly valued:
Signal processing Image processing Numerical algorithms Scientific computing Physics-based simulation Experience with embedded computing platforms, high-bandwidth data paths, FPGA environments, or hardware-software co-design is considered an advantage. You communicate clearly and are comfortable working in multidisciplinary and international engineering teams. What can you expect from TMC?
TMC combines the security of permanent employment with the opportunity to work on challenging projects within leading high-tech environments. As an Employeneur, you can expect:
Individual profit sharing A personal training and development budget Technical and professional coaching Access to a strong network of high-tech professionals The opportunity to work on complex and innovative engineering projects Freedom to actively shape your own professional development
#J-18808-Ljbffr
GPU programming
and
CUDA
optimization? Do you enjoy working on performance-critical software where mathematics, algorithms, and hardware come together? At TMC, we are looking for a
Senior GPU / CUDA Software Engineer
to work on advanced high-tech applications where processing speed, scalability, and reliability are essential. What will you do?
In this role, you will design, develop, and optimize high-performance C++ and CUDA software for GPU-accelerated applications. You will work on computationally intensive algorithms in areas such as signal processing, image processing, numerical modelling, and AI, translating them into efficient GPU implementations. Your responsibilities will include:
Developing and optimizing high-performance C++ and CUDA software Designing and improving CUDA kernels for maximum execution efficiency Profiling CPU and GPU workloads to identify performance bottlenecks Optimizing memory usage, bandwidth, synchronization, and CPU-GPU data transfers Improving latency, throughput, scalability, and overall resource utilization Applying parallelization, vectorization, computation reuse, and kernel fusion techniques Maintaining numerical accuracy and output quality while improving performance Working closely with FPGA, electronics, firmware, systems, algorithm, and AI engineers Contributing to hardware-software partitioning and complete system architectures What do we expect from you?
A Master's degree or PhD in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, Physics, Biomedical Engineering, or a related technical field Strong professional experience with C++ Deep hands-on experience with CUDA and GPU programming Strong knowledge of CUDA performance optimization, including: memory hierarchy memory bandwidth occupancy CUDA streams CPU-GPU data transfer Experience with profiling and performance-analysis tools Strong understanding of object-oriented software design and maintainable software architecture A solid mathematical foundation Experience in one or more of the following areas is highly valued:
Signal processing Image processing Numerical algorithms Scientific computing Physics-based simulation Experience with embedded computing platforms, high-bandwidth data paths, FPGA environments, or hardware-software co-design is considered an advantage. You communicate clearly and are comfortable working in multidisciplinary and international engineering teams. What can you expect from TMC?
TMC combines the security of permanent employment with the opportunity to work on challenging projects within leading high-tech environments. As an Employeneur, you can expect:
Individual profit sharing A personal training and development budget Technical and professional coaching Access to a strong network of high-tech professionals The opportunity to work on complex and innovative engineering projects Freedom to actively shape your own professional development
#J-18808-Ljbffr
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