Senior Data Scientist - Computer Vision

We are looking for a highly skilled Senior Data Scientist with strong expertise in Computer Vision and Deep Learning to design, develop, and deploy scalable AI solutions. The ideal candidate should have hands-on experience in building production-grade deep learning models for image and video analytics use cases and implementing MLOps best practices within Azure-based environments. This role requires strong problem-solving capabilities, architectural thinking, and experience working with large-scale datasets and cloud-native platforms. Key Responsibilities : - Design, develop, and deploy advanced deep learning models for computer vision use cases including : - Image Classification - Object Detection - Image Segmentation - Video Analytics - Build scalable ML pipelines using Databricks, MLflow, and Delta Lake. - Perform data preprocessing, augmentation, feature engineering, and optimization for large-scale image/video datasets. - Implement model training, validation, hyperparameter tuning, and performance benchmarking. Apply modern computer vision techniques including : - CNN architectures - Transfer Learning - Transformer-based Vision Models (e.g., ViT) - Implement and manage MLOps best practices, including: - Model versioning - CI/CD pipelines - Automated deployment - Monitoring and retraining strategies - Work closely with cross-functional teams including engineering, product, and business stakeholders. - Optimize models for performance, scalability, and cost efficiency in Azure cloud environments. - Ensure adherence to coding standards, documentation, and best practices. Required Technical Skills : - Strong programming expertise in Python. Hands-on experience with deep learning frameworks : - TensorFlow - PyTorch - Keras - Strong knowledge of computer vision algorithms and architectures. - Experience with: - Databricks Notebooks - MLflow - Delta Lake - Solid understanding of MLOps frameworks and deployment workflows. - Experience handling large-scale image and video datasets. - Familiarity with UNIX/Linux environments and command-line automation. - Strong problem-solving and analytical skills. Cloud & Infrastructure : - Strong expertise in Azure Cloud ecosystem. - Experience working with cloud-native AI/ML services in Azure. - Knowledge of containerization and orchestration (Docker/Kubernetes is a plus). Good to Have : - Exposure to Natural Language Processing (NLP). - Experience with transformer-based multimodal models. - Experience working in enterprise-scale AI implementations. - Knowledge of Git-based workflows and DevOps practices. Soft Skills : - Strong communication and stakeholder management skills. - Ability to lead technical discussions and mentor junior team members. - Self-driven with a strong sense of ownership and accountability. .