Lead Embedded AI Engineer

Position Title : TinyML / Embedded AI Principal Engineer

Location : Bangalore

Experience Required : 15+ Years

Employment Type : Full-Time

Role Purpose :

The TinyML / Embedded AI Principal Engineer will lead the design, development, optimization, and deployment of AI solutions on edge and resource-constrained embedded devices. This role is critical to enabling real-time, mission-critical AI inference across advanced programs, with a focus on sensor fusion, hardware-software co-design, and embedded intelligence under strict latency, power, and memory constraints.

Key Responsibilities :

• Architect and deploy TinyML / Embedded AI models for real-time inference on microcontrollers, SoCs, FPGAs, and custom accelerators.
• Optimize AI models using quantization, pruning, and compression for performance and efficiency.
• Select and integrate embedded AI hardware platforms (e.G., NVIDIA Jetson, ARM Ethos-U, Kendryte, FPGA, ASIC).
• Develop real-time computer vision and multi-sensor fusion algorithms (video, radar, LiDAR, IMU).
• Implement robust object detection, classification, and tracking under challenging conditions.
• Integrate AI into embedded / mechatronic systems ensuring reliability, scalability, and security.
• Lead HIL simulations, lab validation, and field testing of embedded AI systems.
• Mentor junior engineers and drive capability growth across the organization.
• Serve as technical authority on embedded AI deployment and optimization strategies.
• Produce technical documentation, risk assessments, and stakeholder reports.
• Research and adopt emerging TinyML frameworks (TensorFlow Lite Micro, Edge Impulse, PyTorch Mobile).
• Collaborate with cross-functional teams to design next-gen AI-enabled embedded architectures.
• Generate risk / progress reports and propose mitigation strategies.

Experience & Skills :

Qualifications :