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.

• 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.