TinyML / Embedded AI Principal Engineer

TinyML / Embedded AI Principal Engineer

Location: UAE (Relocation Mandatory)

Candidate MUST be willing to relocate to the United Arab Emirates — this is a highlighted requirement for this position.

We are seeking an accomplished TinyML / Embedded AI Principal Engineer to lead advanced AI initiatives for mission‑critical defence programs. This role focuses on designing, optimizing, and deploying AI models on resource‑constrained embedded platforms while ensuring real‑time, reliable system performance.

Mandatory Requirement – Relocation to UAE The selected candidate MUST relocate to the UAE.

Remote or hybrid arrangements are not available for this role due to on‑site program requirements, hardware integration, and defence‑grade project dependencies.

Please apply only if you are open to relocating.

Role Overview The engineer will design, optimize, and deploy TinyML / Embedded AI solutions across microcontrollers, SoCs, FPGAs, and custom hardware accelerators, supporting full lifecycle engineering from model design to field deployment.

Key Responsibilities

Embedded AI & Model Optimization • Develop and deploy TinyML models for real-time inference on MCUs, SoCs, FPGAs, and accelerators. • Apply quantization, pruning, and compression to meet strict power and memory limits. • Research and adopt TinyML frameworks such as TensorFlow Lite Micro, Edge Impulse, PyTorch Mobile . Hardware Integration • Integrate AI models on NVIDIA Jetson, ARM Ethos‑U, Kendryte, FPGA/ASIC accelerators . • Lead hardware–software co-design to enable real-time AI workloads. Computer Vision & Sensor Fusion • Develop algorithms for video, radar, LiDAR, IMU fusion and real-time perception. • Implement robust detection, tracking, and classification under mission constraints. Systems Engineering & Testing • Lead HIL simulations, lab validation, field testing and qualify AI systems for deployment. • Produce technical documentation, risk assessments, and performance reports. Leadership • Mentor junior engineers and provide technical authority for embedded AI solutions.

Required Expertise • 15+ years in embedded AI / defence systems development. • Expert in ML/DL, computer vision, sensor fusion, real-time inference, and AI optimization. • Experience with toolchains such as TensorRT, CMSIS-NN, OpenVINO, Vitis AI . • Strong programming skills in Python, C/C++ , and embedded engineering. • Deep knowledge of system engineering processes (qualification, validation, field testing).

Preferred Qualifications • Master's or PhD in Computer Science, Electrical/Computer Engineering , or related fields. • Certifications in TinyML / embedded systems / hardware acceleration are a plus.

Industry Requirement

Must have worked on defence or aerospace applications.

Profiles from other industries will not be considered.