AI Engineer Edge AI

Job Description You will be joining GFO Innovative Research and Development Pvt. Ltd. as an AI Engineer, where you will be focusing on Artificial Intelligence, Embedded Systems, and Edge AI products. Your responsibilities will include working on the entire AI lifecycle, from data collection and labeling to model deployment, MLOps, and product testing on real hardware platforms such as ESP32, Raspberry Pi, and NVIDIA Jetson. Key Responsibilities - Assist in developing, training, and evaluating ML / Deep Learning models - Work on Computer Vision and sensor-based AI applications - Perform data preprocessing, cleaning, labeling, and augmentation - Collect real-world data from cameras, sensors, and IoT devices - Optimize AI models for latency, accuracy, and edge deployment - Assist in deploying models using Docker, APIs, and edge AI pipelines - Monitor model performance and assist in continuous improvement - Help maintain model lifecycle workflows (training testing deployment) - Work with ESP32 microcontrollers for data acquisition and control - Interface AI systems with electronic hardware, sensors, cameras, and actuators - Understand and debug hardwaresoftware integration - Perform functional testing and validation of AI-based products - Test AI models under real-world environmental conditions - Assist in system reliability, performance benchmarking, and bug fixing - Support field testing and on-device debugging Required Qualifications - Bachelors degree in Electronics & Communication Engineering (ECE) or related field - Strong understanding of: - Digital Electronics - Basic communication concepts - Programming skills in Python - Hands-on or academic experience with Edge devices - Familiarity with Linux-based systems - Basic understanding of Machine Learning & AI concepts Mandatory Technical Skills - ESP32 programming (Arduino / ESP-IDF basics) - Python for: - Data handling - Automation scripts - Data labeling and dataset management - Linux command-line usage - Understanding of AI model training and inference workflows Preferred / Good-to-Have Skills - Computer Vision: OpenCV - ML frameworks: PyTorch / TensorFlow - Edge AI tools: TensorRT, DeepStream, ONNX - MLOps tools: Docker, Git, basic CI/CD concepts - Experience with: - Raspberry Pi / NVIDIA Jetson - Camera sensors & electronic modules - Basic cloud or API integration knowledge Who Should Apply - ECE graduates interested in AI + Electronics + Embedded Systems - Candidates with AI + hardware projects - Freshers eager to work on end-to-end AI product development - Engineers interested in edge AI, IoT, and real-world deployments What We Offer - Hands-on experience with production AI systems - Exposure to MLOps, embedded AI, and product lifecycle - Opportunity to work with real hardware and real data - Mentorship and structured learning environment - Growth path into AI Engineer / Embedded AI Engineer / MLOps roles Job Description You will be joining GFO Innovative Research and Development Pvt. Ltd. as an AI Engineer, where you will be focusing on Artificial Intelligence, Embedded Systems, and Edge AI products. Your responsibilities will include working on the entire AI lifecycle, from data collection and labeling to model deployment, MLOps, and product testing on real hardware platforms such as ESP32, Raspberry Pi, and NVIDIA Jetson. Key Responsibilities - Assist in developing, training, and evaluating ML / Deep Learning models - Work on Computer Vision and sensor-based AI applications - Perform data preprocessing, cleaning, labeling, and augmentation - Collect real-world data from cameras, sensors, and IoT devices - Optimize AI models for latency, accuracy, and edge deployment - Assist in deploying models using Docker, APIs, and edge AI pipelines - Monitor model performance and assist in continuous improvement - Help maintain model lifecycle workflows (training testing deployment) - Work with ESP32 microcontrollers for data acquisition and control - Interface AI systems with electronic hardware, sensors, cameras, and actuators - Understand and debug hardwaresoftware integration - Perform functional testing and validation of AI-based products - Test AI models under real-world environmental conditions - Assist in system reliability, performance benchmarking, and bug fixing - Support field testing and on-device debugging Required Qualifications - Bachelors degree in Electronics & Communication Engineering (ECE) or related field - Strong understanding of: - Digital Electronics - Basic communication concepts - Programming skills in Python - Hands-on or academic experience with Edge devices - Familiarity with Linux-based systems - Basic understanding of Machine Learning & AI concepts Mandatory Technical Skills - ESP32 programming (Arduino / ESP-IDF basics) - Python for: - Data handling - Automation scripts - Data labeling and dataset management - Linux command-line usage - Understanding of AI model trainin