Principal Engineer - TinyML / Embedded AI EDGE Group PJSC

Design, implement, and deploy TinyML / Embedded AI models for real-time inference on microcontrollers, SoCs, FPGAs, and custom accelerators.

Apply quantization, pruning, and compression techniques to optimize speed, power efficiency, and memory footprint for embedded AI models..

Select and integrate embedded AI hardware accelerators (e.g., NVIDIA Jetson, ARM Ethos-U, Kendryte, FPGA, ASIC).

Develop and deploy real-time CV and multi-sensor fusion algorithms for video, radar, LiDAR, IMU, and other modalities.

Implement robust object detection, classification, and tracking under challenging conditions.

Integrate AI solutions into embedded/mechatronic systems, ensuring reliability, scalability, and security.

Lead hardware-in-the-loop (HIL) simulations, lab validation, and field qualification testing for embedded AI systems.

Mentoring and training of junior technical personnel.

Provide technical authority for embedded AI deployment, hardware-software co-design, and AI optimization strategy.

Produce technical documentation, risk assessments, and progress reports for internal and external stakeholders..

Research and adopt emerging TinyML frameworks (e.g., TensorFlow Lite Micro, Edge Impulse, PyTorch Mobile) and edge AI toolchains.

Collaborate with cross-functional teams to design AI-enabled embedded architectures for next-gen systems.

Generation of risk/progress reports, presentations and initiate proposals of mitigation action.