AI Engineer

Job Description

Key Responsibilities Design, train, and optimize deep learning models (CNNs, SSD and related variants) for image classification and object detection. Implement and maintain end-to-end computer vision pipelines using OpenCV or equivalent libraries. Develop, deploy, and manage models using Azure Custom Vision and other cloud platforms. Handle full model lifecycle: versioning, repository management, CI/CD integration, and OTA deployment. Work closely with cross-functional teams to integrate AI models into production environments. Monitor and evaluate model performance; retrain models to ensure accuracy and reliability. Maintain comprehensive documentation of workflows, experiments, and deployment processes for reproducibility and compliance. Required Skills & Qualifications Bachelor?s or Master?s degree in Computer Science, AI, Data Science, Machine Learning, IT , or related fields. 2?3 years of hands-on experience in computer vision, deep learning, and model deployment . Strong programming proficiency in Python . Experience with TensorFlow, PyTorch, and Azure Custom Vision . Solid understanding of deep learning architectures (e.g., CNN, SSD ). Familiarity with MLOps practices: Git, CI/CD, model versioning, OTA deployment . Proficiency in image processing and vision techniques using OpenCV or equivalent libraries. Experience in model evaluation, tuning, and real-world deployment. Experience with cloud platforms such as Azure, AWS, or GCP . Exposure to edge deployment / embedded AI systems. Understanding of dataset management and data annotation tools. Familiarity with containerization ( Docker ) and orchestration ( Kubernetes ) is a plus. Soft Skills Strong problem-solving and debugging skills. Excellent communication and collaboration abilities. High attention to detail and ability to work in a fast-paced environment. Commitment to writing clean, maintainable, and scalable code. Curiosity and eagerness to learn and explore emerging industry trends.