Data Scientist (Computer Vision)

Role Overview

We are seeking a Data Scientist with expertise in Computer Vision and AI to design, develop, fine-tune, and deploy machine learning and deep learning solutions. The role involves building scalable AI models, working with large image/video datasets, and collaborating with cross-functional teams to deliver business-focused AI applications. The ideal candidate should have strong experience in computer vision, deep learning frameworks, and MLOps practices.

Responsibilities

• Design, develop, and optimize AI/ML solutions for computer vision applications.
• Build and fine-tune deep learning models for image classification, object detection, and image segmentation.
• Process, clean, annotate, and manage large-scale image and video datasets.
• Develop data preprocessing and post-processing pipelines.
• Train, evaluate, and validate machine learning and deep learning models.
• Monitor model performance using relevant evaluation metrics and conduct error analysis.
• Perform experimentation, benchmarking, and model comparison activities.
• Deploy and scale AI models in production environments using cloud and MLOps practices.
• Collaborate with engineering, product, and business teams to integrate AI solutions.
• Follow software development best practices including version control, testing, documentation, and reproducibility.

Requirements

• 3-8 years of experience.
• Strong proficiency in Python.
• Hands-on experience with Computer Vision and Deep Learning.
• Expertise in PyTorch, TensorFlow, or Keras.
• Experience with OpenCV and image processing techniques.
• Strong knowledge of image classification, object detection, image segmentation, transfer learning, and model fine-tuning.
• Experience with ML model evaluation and performance optimization.
• Knowledge of Git and software development best practices.
• Understanding of MLOps concepts and production deployment.

Nice to Have

• Experience with Vision-Language Models (VLMs) and Multimodal AI.
• Exposure to Large Language Models (LLMs) and NLP concepts.
• Experience with MLflow, Kubeflow, Docker, and Kubernetes.
• Cloud platform exposure (AWS, Azure, or GCP).
• Experience in healthcare, medical imaging, or similar domain-specific AI applications.
• Research publications or contributions to open-source AI projects.
• Knowledge of Responsible AI and AI ethics.

Skills

• Python
• PyTorch
• TensorFlow
• OpenCV
• MLOps