Conscientious and innovative deep learning engineer with extensive experience in defining data requirements, collecting, labeling, augmenting, processing, and using the processed data in validating predictive models and deploying completed models to deliver business impact. The candidate is well-versed in software design paradigms and good development practices such as construction, feature detection, segmentation, and classification in machine learning and deep learning. Experienced in algorithm evaluation, preparation, analysis, modeling, and execution.
Experience
Deep Learning Engineer
Magnifi AI
Work Actively as a part of the Computer Vision and Deep Learning Team to Train Computer Vision Models. Work closely with the Data Sampling Team for Appropriate Dataset Collection. Implementation of the SOTA Architectures for Model Training.
Deep Learning Engineer
Artivatic AI
Completely handling 3 API services in Project Alfred focusing on health-related OCR documents, including doctor letters, medical certificates, receipts, and imaging reports processing and documentation. Conceptualized and deployed an updated and newer version of KIE-based model text extraction from Receipt documents. Integrated the text extraction/ data and post-processing steps like Spell Correction and Elimination of Similar words. Developing novel algorithms and modeling techniques, as well as performing documentation of text extraction via image recognition, object identification, and visual recognition. Collaborating with R&D and Machine Learning engineers implementing algorithms to enhance user and developer experience. Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
Deep Learning Engineer - Intern
Skylark Drones
Facilitated a literature survey followed by benchmarking different Image Segmentation SOTA algorithms and benchmarked the same model from different open-source repositories. Promoted to Haul roads project aiming at Image Segmentation on geospatial data and built the initial model. Administrated the modification of the codebase to train a model on a 4-channel RGBA image rather than a 3-channel RGB image with 4 channels having slope information from geospatial metadata.
Data Scientist Intern
CrowdANALYTIX
Supported 6 projects for Company’s Collexion AI platform, which is the world’s largest retail AI marketplace for no-code, production-ready AI models. Indulged in creating AI models based on Face Detection, Age Estimation, Pedestrian Tracking, Image Quality Assessment, Product Centering, and Shadow Generation. Performed Extensive Literature Survey of papers and codebases to find an efficient model to do Shadow Generation.
Education
National Institute of Technology, Surat
Bachelor of Technology
Computer Engineering
Licenses & Certifications
Deep Learning Specialization
Andrew Ng
GANs Specialization
Sharon Zhou
NVIDIA DLI Workshop on Building Transformers-based Natural Language Processing Applications
NVIDIA
NVIDIA DLI Workshop on Fundamentals of Accelerated Data Science with RAPIDS
NVIDIA