TinyML / Embedded AI Principal Engineer

About the job

TinyML / Embedded AI Principal Engineer 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. **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.

Requirements

• Embedded AI
• TinyML
• Machine Learning
• Deep Learning
• Python
• C/C++

Qualifications

• Master's or PhD in Computer Science or related fields
• Certifications in TinyML

Preferred Technologies

• Embedded AI
• TinyML
• Machine Learning
• Deep Learning
• Python
• C/C++

About the company

L&T Technology Services is a leading global engineering services company providing innovative and technology-driven solutions to clients across various industries with a focus on digital transformation.