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Job Summary: Join our team as a Senior Data Scientist specializing in Computer Vision, where you will lead the design, development, and deployment of cutting-edge vision-based machine learning models. In this role, you will tackle complex real-world business challenges by building scalable AI solutions. We are looking for an expert with a deep understanding of image and video processing who can seamlessly bridge the gap between technical innovation and business impact. Role & responsibilities Develop and deploy sophisticated computer vision models for tasks including object detection, image classification, segmentation, OCR, and real-time video analytics. - Manage large-scale datasets by overseeing collection, annotation strategies, cleaning, and data augmentation to ensure high-quality model training. - Architect and optimize deep learning frameworks such as CNNs, Vision Transformers, GANs, and YOLO for production-ready environments. - Collaborate with cross-functional engineering, product, and MLOps teams to integrate vision models into end to-end production pipelines. Enhance model performance and scalability through quantization, pruning, and conversion for edge deployment using ONNX or TensorRT. Execute rigorous experiments and statistical analyses, including A/B testing, to validate model accuracy and assess business outcomes. - Keep abreast of state-of-the-art research in computer vision and deep learning to identify and implement innovative solutions for business problems. - Mentor junior scientists and establish best practices for robust model development, evaluation, and documentation. - Partner with data engineering to build high-performance, scalable data pipelines tailored for vision workloads. Preferred candidate profile 7+ years of qualified experience in Machine Learning with a specialization in Computer Vision. Advanced degree (Master's or Ph.D. preferred) in Computer Science, Electrical Engineering, or a related quantitative field. Expert proficiency in Python and frameworks like PyTorch, TensorFlow, or Keras. Hands-on experience with CV libraries such as OpenCV, YOLO, Detectron2, and MMDetection. Strong background in CNNs, Vision Transformers (ViT), and image preprocessing techniques. Proven experience deploying models via Docker, Kubernetes, FastAPI, ONNX, and TensorRT. Skilled in cloud AI/ML services across AWS, GCP, or Azure (e.g., SageMaker, Vertex AI). Deep knowledge of data structures, algorithms, and software engineering best practices. Experience managing large datasets with SQL, Spark, Pandas, or Dask. History of taking ML models from research/prototypes into scalable production environments. Excellent communication, problem-solving, and cross-functional collaboration skills. Familiarity with MLOps, CI/CD pipelines, and edge AI hardware (NVIDIA Jetson, mobile inference). .