• Design, develop, test embedded applications and algorithm libraries both pre and post silicon;
• In-depth performance analysis and optimization for dedicated heterogeneous platforms which include DSPs and Accelerators
• Implement and performance-tune parallel programming framework on embedded platforms and multi-core architectures.
• Evaluate state of the art deep learning, driver identification, Predictive Maintenance algorithms;
• Deploy and optimize machine learning models on resourceconstrained embedded systems
Must have skills:
• Experience with at least one embedded ML framework (TensorFlow Lite, PyTorch Mobile, or ONNX Runtime)
• Understanding of model quantization and optimization techniques for embedded deployment
• Good knowledge of processor architecture and micro-architecture (Ex: SIMD/GPGPU/NEON);
• 5+ hands-on experience in software design and development on complex embedded computing platforms
• Mathematical background and good understanding of how algorithms work (for example: image processing or neural network)
Any of the following are pluses:
• Experience with ML optimization tools like TVM, MLIR, or vendor-specific ML compilers
• Prior work/projects on Intelligence/Machine Learning, DSP algorithms or Audio processing;
• Knowledge of software design and development on complex embedded computing platforms, including performance optimization;
• Knowledgeable about Automotive SPICE, Functional Safety (ISO-26262), Standard Coding Guidelines such as defined by MISRA or AUTOSAR, or equivalent standards relative in your field of expertise.
• Knowledge in performance optimization on embedded platforms with ARM NEON or accelerator/DSP;
• Electronic hardware background or close to hardware level
