Master’s Degree or foreign equivalent in Computer Science, Electrical Engineering, Electronics Engineering or related field and 6 months of experience in the job offered or related occupation.
Education and/or experience must include:
Fundamental components and structure of novel Machine Learning models for Vision and Large Language Model applications
Modern ML frameworks to develop and test ML models, such as PyTorch or CoreML
Familiarity with computer architecture, processors, GPU’s, FPGA’s, peripheral devices, their interfaces in System on Chip micro-architectures and their performance metrics, including bandwidth, throughput and power consumption
Using the main hardware components of the modern processing engines for Machine Learning applications, including the processor, GPU, and memory.
Performing trade-off analysis between power, performance, and latency for different ML models and processors/GPU’s
Profiling the performance of all layers in a deep Neural Networks to identify performance bottlenecks and need optimization.
Modern parallel programming paradigms used in ML applications, including CUDA
Analyzing and fine-tuning of the execution of software tasks on parallel compute engines in hardware, including processors and GPU’s
Utilizing Python and C/C++ programming languages
Using operating systems including Linux, and software version control, including Git