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Accelerate Machine Learning Workflows with Expert GPU Programming
3 weeks ago
We are seeking an experienced professional to develop, optimize and deploy GPU-accelerated solutions for high performance machine learning workloads.
- Develop and maintain GPU-accelerated components using frameworks such as CUDA, HIP or OpenCL
- Analyze and improve kernel performance through profiling, benchmarking and resource optimization
- Optimize memory access, compute throughput and kernel execution to improve overall system performance on target GPUs
- Bachelor's or master's degree in Computer Science, Electrical Engineering or a related field
- 3+ years of hands-on experience in GPU programming using CUDA, HIP, OpenCL or other GPU compute APIs
- Strong understanding of GPU architecture, memory hierarchy and parallel programming models
PREFERRED QUALIFICATIONS:
- Familiarity with cuDNN, TensorRT, OpenCL or other GPU computing libraries
- Exposure to AI/ML workloads, computer vision or video/image processing
WE OFFER: A challenging role that requires expertise in GPU programming, strong problem-solving skills and the ability to work collaboratively.