AI Engineer
1 week ago
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.
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