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Metro location and attractive ML/CV role draw applicants, but biomedical imaging niche reduces overall competition.
Core ML/CV skills transfer across industries, but biomedical imaging experience significantly influences fit.
Specific ML/CV skills and biomedical imaging familiarity required, but years flexibility keeps filters moderate.
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Develop custom computer vision algorithms and image analysis pipelines for biomedical imaging using Python, OpenCV, and deep learning frameworks.
Work with diverse biomedical imaging datasets including microscopy, MRI, CT, and PET scans to perform segmentation, feature extraction, and quantitative analysis.
Collaborate with scientists and AI researchers to design and fine-tune deep learning and vision foundation models tailored to biomedical research challenges.
B.E./B.Tech./M.Tech./M.S. in Computer Science, AI, Computer Vision, Electronics, Electrical Engineering, Biomedical Engineering, or related fields.
Programming proficiency in Python with hands-on experience in OpenCV.
Knowledge and practical experience in computer vision, image processing, machine learning, and deep learning, including frameworks like PyTorch.
Work Experience Required: Freshers to 5 years relevant experience including academic projects, internships, or industry experience.
Has practical experience applying computer vision techniques to biomedical imaging problems using custom-built algorithms rather than only off-the-shelf tools.
Capable of independently developing and optimizing deep learning models for segmentation and feature extraction in biomedical datasets.
Comfortable collaborating with cross-disciplinary teams including scientists and domain experts to translate research challenges into technical solutions.