AI Engineer

We are seeking a talented and driven AI Engineer with 2+ years of experience in Python, Computer Vision, Object Detection, and Software Development to join our innovative team. The ideal candidate will have hands-on experience in building AI solutions, optimizing machine learning models, and deploying scalable applications. Key Responsibilities: Develop and implement machine learning algorithms and computer vision models for real-time processing. Build and optimize Object Detection models such as YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), Faster R-CNN, and more. Collaborate with cross-functional teams to design, build, and deploy AI-driven software solutions. Integrate Object Detection capabilities into software applications for automation and smart analytics. Perform data preprocessing, image augmentation, and model evaluation. Optimize and fine-tune YOLO models for speed and accuracy in real-world scenarios. Maintain and improve code quality, organization, and automation. Troubleshoot issues and provide solutions to complex technical challenges. Document AI models, software architecture, and development processes. Key Skills Proficiency in Python and its libraries (NumPy, Pandas, OpenCV, TensorFlow, PyTorch). Solid understanding of Computer Vision concepts and image processing techniques. Hands-on experience with Object Detection models like YOLO, SSD, Faster R-CNN, and custom model training. Experience in Software Development and version control (Git). Familiarity with REST APIs, database management, and cloud deployment. Knowledge of Machine Learning algorithms and deep learning architectures. Strong problem-solving skills and the ability to debug complex systems. Excellent communication skills and ability to work in a collaborative environment. Preferred Skills: Experience with Docker, Kubernetes, or other containerization technologies. Exposure to Cloud Platforms (AWS, GCP, Azure) for model deployment. Understanding of MLOps best practices for production-grade deployments. Familiarity with Edge AI deployment (Jetson Nano, Raspberry Pi, etc.). Knowledge of Data Engineering and ETL processes. Experience with Model Optimization Techniques like TensorRT, ONNX.