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.