About the role
Indus Towers is seeking an experienced Principal Data Scientist - Computer Vision to lead the development and deployment of advanced AI and computer vision solutions. The role will focus on solving complex business problems through image and video analytics, deep learning, and scalable machine-learning systems. The ideal candidate will have strong hands-on expertise in computer vision, model deployment, MLOps, and technical leadership.
Responsibilities:
- Lead the end-to-end development of computer vision solutions, from problem definition and data preparation to model deployment and performance monitoring.
- Design, develop, and optimise models for image classification, object detection, image segmentation, OCR, video analytics, object tracking, and anomaly detection.
- Build scalable pipelines for image/video ingestion, annotation, preprocessing, training, evaluation, and inference.
- Develop deep learning models using CNNs, Vision Transformers, multimodal models, and modern computer vision techniques.
- Collaborate with data engineers, ML engineers, software engineers, product teams, and business stakeholders to deploy production-grade AI solutions.
- Improve model accuracy, latency, scalability, and cost efficiency across cloud and edge environments.
- Define best practices for experimentation, model versioning, deployment, monitoring, retraining, and governance.
- Evaluate emerging AI technologies, computer vision frameworks, and foundation models for relevant business use cases.
- Mentor and provide technical guidance to data scientists and machine learning engineers.
- Present technical recommendations, solution architecture, and project outcomes to senior stakeholders.
Requirements:
- Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, or a related field.
- 8+ years of experience in Data Science, Machine Learning, AI, or Computer Vision.
- Strong practical experience in computer vision, image processing, and deep learning.
- Expertise in Python and working knowledge of SQL.
- Hands-on experience with PyTorch, TensorFlow, Keras, or similar deep learning frameworks.
- Experience with OpenCV, YOLO, Detectron2 MMDetection, TensorRT, ONNX, or similar computer vision tools.
- Strong understanding of image classification, object detection, segmentation, OCR, video analytics, tracking, and anomaly detection.
- Experience with CNNs, Vision Transformers, transfer learning, self-supervised learning, and vision-language models.
- Experience deploying ML models using Docker, Kubernetes, MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar tools.
- Strong knowledge of MLOps, CI/CD, model monitoring, data drift, model retraining, and model governance.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Proven ability to lead complex technical projects and mentor team members.