
Advanced Machine Learning Solutions Developer
2 days ago
We are seeking a skilled GPU programming engineer to develop and optimize high-performance machine learning workloads.
The ideal candidate has strong expertise in GPU programming across one or more platforms, including NVIDIA CUDA, AMD ROCm/HIP, or OpenCL. Experience with parallel computing, performance tuning, and ML system integration is also required.
- Key Responsibilities:
- Develop and optimize GPU-accelerated components for machine learning pipelines using frameworks such as CUDA, HIP, or OpenCL.
- Analyze and improve GPU kernel performance through profiling, benchmarking, and resource optimization.
- Optimize memory access, compute throughput, and kernel execution to improve overall system performance on the target GPUs.
- Port existing CPU-based implementations to GPU platforms while ensuring correctness and performance scalability.
- Bachelor's or Master's Degree: In computer science, electrical engineering, or a related field.
- Experience: 3+ years of hands-on experience in GPU programming using CUDA, HIP, OpenCL, or other GPU compute APIs.
- Skills: Strong understanding of GPU architecture, memory hierarchy, and parallel programming models. Proficiency in C/C++ and hands-on experience developing on Linux-based systems.
- Familiarity: With profiling and tuning tools such as Nsight, rocprof, or Perfetto.
- Familiarity: With cuDNN, TensorRT, OpenCL, or other GPU computing libraries.
- Experience: With AI/ML workloads, computer vision, or video/image processing.
- Knowledge: Of OpenACC, SYCL, or other directive-based programming models.
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