Principle Applied Scientist

4 weeks ago


Bengaluru, Karnataka, India RadiusAI Full time

About Us We are an innovative company revolutionising retail checkout experiences by replacing traditional barcodes with cutting-edge Computer Vision technology Our platform enables seamless faster and smarter checkout processes enhancing the shopping experience for both retailers and consumers We re growing rapidly and are looking for an experienced Android Cross-Platform App Developer to join our team and help us build the future of retail technology Key Responsibilities Lead the research design and development of advanced computer vision models for tasks like object detection tracking segmentation OCR scene understanding and 3D vision Translate business needs into scalable scientific solutions using state-of-the-art deep learning and classical computer vision techniques Design and implement experiments to evaluate performance robustness and accuracy of CV models in real-world production scenarios Collaborate with cross-functional teams including software engineering product and data teams to integrate vision models into applications Drive innovation through internal IP generation patents publications and contribute to the long-term AI ML roadmap Provide scientific and technical leadership mentoring junior scientists and reviewing designs and architectures Stay up to date with latest developments in AI deep learning and computer vision through academic and industrial research e with industry best practices and emerging technologies to drive continuous improvement Qualifications M S or Ph D in Computer Science Electrical Engineering or a related field with specialization in Computer Vision or Machine Learning 5 years of hands-on experience in building and deploying production-grade computer vision models Strong theoretical background and applied experience in deep learning frameworks e g PyTorch and model architectures e g CNNs Vision Transformers Diffusion Models Experience in working with large-scale datasets training pipelines and performance evaluation metrics Proficiency in Python and scientific computing libraries e g NumPy OpenCV scikit-learn Experience with model optimization for edge deployment ONNX TensorRT pruning quantization is a strong plus Strong written and verbal communication skills with a track record of mentoring and collaboration Preferred Qualifications Experience with computer vision in real-time systems e g AR VR robotics automotive surveillance Published research papers in top-tier conferences CVPR ICCV NeurIPS etc Exposure to MLOps or ML model lifecycle in production environments Familiarity with cloud platforms AWS GCP Azure and containerization tools Docker Kubernetes and basic bash scripting



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