Our client is transforming how communities protect students and enforce traffic safety—through intelligent, real-time video analytics and automated enforcement. As part of this mission, we are advancing the shift from cloud-dependent AI to intelligent edge computing.

We're looking for an Embedded AI Engineer to lead the development and deployment of deep learning models on IoT and edge computing platforms. You'll work on converting and optimizing computer vision models—such as CNNs, YOLO, RNNs, and OCR—for execution on high-efficiency hardware accelerators like Hailo, NVIDIA Jetson, Client Movidius, or ARM-based NPUs.

This role is central to scaling our client's next-generation Edge AI platform, enabling real-time safety decisions and unlocking current capabilities for school bus fleets, student safety, and public transportation environments.

Key Responsibilities

- Develop and optimize embedded software and AI model inference pipelines for real-time object detection, tracking, and classification at the edge.

- Deploy and maintain vision-based deep learning models (YOLO, CNN, RNN, OCR) on resource-constrained devices using AI accelerators (e.g., Hailo, Jetson, Coral, ARM).

- Lead cloud-to-edge transformation of AI models, including quantization, pruning, conversion, and hardware-aware optimization.

- Collaborate with AI/ML researchers to integrate trained models into embedded applications and validate edge inference accuracy.

- Optimize for performance, latency, and power efficiency in real-world mobile or vehicle-mounted environments.

- Work with hardware abstraction layers, toolchains, and SDKs for AI acceleration (e.g., HailoRT, TensorRT, OpenVINO, ONNX, TFLite).

- Design and implement robust,



fault-tolerant inference pipelines using tools like GStreamer, OpenCV, or FFmpeg.

- Contribute to system architecture discussions focused on scalable AI at the edge, real-time event capture, and safety-critical decision support.

Preferred Qualifications

- Proficient in C/C++ and Python for embedded development and AI integration.

- Experience with quantization, pruning, and model conversion for edge inference (ONNX, TFLite, TensorRT, Dataflow Compiler etc.).

- Hands-on experience with at least one AI hardware platform (e.g., Hailo, NVIDIA Jetson, Client Movidius, ARM Ethos-U, Google Coral).

- Solid understanding of deep learning architectures and model behavior (CNN, YOLOv5/v8, OCR, ReID, RNNs).

- Strong knowledge of video/image processing pipelines using GStreamer, OpenCV, or similar.

- Experience working with Linux-based embedded systems, build systems (Yocto, CMake), and cross-compilation toolchains.

- Understanding of IoT/vehicle edge environments, including system resource constraints, fault tolerance, and field deployment challenges.

- Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, AI, or a related technical field.

Nice to Have

- Familiarity with multi-camera systems, object re-identification, or behavior/event detection at the edge.





- Knowledge of real-time messaging and telemetry systems (MQTT, ZeroMQ, or gRPC).

- Experience in public safety, ADAS, surveillance, or other vision-based safety-critical applications.

- Familiarity with data privacy, security, and compliance concerns for edge AI systems.

Emerge seeks, in all its operations, to employ individuals for available positions based on their qualifications, working knowledge, and competency. Emerge has a continuing commitment to ensure that fair and equal employment opportunities are extended to all qualified persons without regard to race, color, religion, sex, gender, sexual orientation, national origin, ethnicity, alienage, citizenship or immigration status, age, mental or physical disability, medical condition, pregnancy, military/veteran status, predisposing genetic characteristics, familial status, marital status, domestic violence victim status, or based on their relationship or association with members of a protected class or any other protected classification, in accordance with applicable federal, state and local laws. Emerge is committed to diversity in its most inclusive sense.

By completing an application with us, you seek to join a team of hardworking professionals dedicated to consistently deliver outstanding service to our customers and contribute to the financial success of the organization, its clients and its employees. Equal access to programs, services and employment is available to all qualified persons. Those applicants requiring accommodation to complete the application and/or interview process should contact our Emerge Recruitment Office.

📌 Embedded AI Engineer (Hyderabad)
🏢 Emerge
📍 Hyderabad