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A CUDA Developer specializes in parallel programming and GPU computing using NVIDIA’s CUDA platform to accelerate compute-intensive applications. This role involves designing, developing, and optimizing algorithms that run efficiently on GPUs, focusing on tasks such as machine learning, scientific simulations, and real-time data processing. The developer writes CUDA kernels, manages memory hierarchy, and ensures efficient thread synchronization and workload distribution. Strong understanding of GPU architecture, performance tuning, and profiling tools is essential to maximize throughput and minimize latency in high-performance computing applications.

  • CUDA C/C++ Programming
  • Parallel Computing Concepts
  • GPU Architecture & Memory Management
  • Kernel Development & Optimization
  • Thread Synchronization & Warp Management
  • Performance Profiling & Debugging (Nsight, Visual Profiler)
  • Integration with Machine Learning Frameworks (TensorFlow, PyTorch)
  • C/C++ Programming