Applied Computer Vision Engineer

Job Description

We, at the LVPEI Center for Innovation, have developed a variety of screening and diagnostic devices Precision imaging systems are crucial components of these devices and the visual information captured here helps the clinician / examiner to decide the status of the eye health To auto-detect and quantify various pathologies of eye we adopt Computer Vision and Machine Learning techniques These developments will help the innovation center to build automated disease detection systems and there by enhance quality of eye care This role gives the candidate an opportunity to work on unique data sets and explore various image processing algorithms and deep learning (algorithms & frameworks) This role majorly involves in organizing data for further analysis, making the models scalable and light-weight to implement them offline on mobile phone platforms Responsibilities Work on translating the computer vision research to its applications in screening and diagnosing eye pathologies. Create novel methods to annotate and organize the patient data for further analysis. Keep UpToDate with the rapid developments in Computer vision and deep learning Incorporate improvements to the model / algorithms design and architecture, leading to increased accuracy in pathology identification. Collaborate with interns at the center to Fastrack the development process. Conceptualize a development task, its dependencies and map out work flows for an assigned project Best practices of software documentation and maintian development logs. Required Skills First-hand experience in working with open source neural networks like ResNet /MobileNet /Inception. Experience of working with at least one among PyTorch / TensorFlow / Keras / MXNet / Theano Strong background in Data Science, data structures, statistics, algorithms like Regression, Classification Sound understanding in the areas of Computer Vision / Pattern Recognition / Image Processing. Online certifications will be an added advantage.