Data Scientist (Computer Vision)

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; Strong analytical and problem-solving abilities; Effective communication and presentation skills; Cross-functional collaboration and stakeholder management; Research-oriented mindset with attention to detail; Ability to work in a fast-paced, dynamic environment; Strong ownership and accountability

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