Highlights:

Skills:Python, C++, C, Java, System Verilog, SQL, CVAT, Eclipse, Google Teachable Machine, MATLAB, Netron, Simulink, Voxel51, CUDA, Git, Linux, ONNX, PyTorch, PTC, TensorRT, TensorFlow, Security Frameworks, Scikit-Learn, Keras, Matplotlib, Seaborn, NumPy, Pandas, OpenCV, Albumentations, Azure, CNN, Computer Vision, Yolov5, Resnet34, Random Forest, Neural Networks, Kivy, Tkinter, Real-Time, Data Visualization, Data Analysis

Machine Learning Engineer 06/2024 - current
Autometrics Manufacturing Inc., , Canada
Industry: Manufacturing
Working as a Machine Learning Engineer building and testing various ML models for welding operations.
• Conducted comprehensive testing on diverse ML and analytical models, including CNN and time series data analysis, ensuring accurate deployment across various platforms. • Collaborated closely with software teams to enhance deployment accuracy and stakeholder satisfaction in machine learning and Artificial Intelligence projects. • Stayed updated with the latest trends, aligning findings with project scopes to implement advanced models and techniques such as Random Forest, resulting in improved outcomes--
Software Engineer Intern 05/2022 - 07/2023
Magna Electronics, , Canada
Industry: Automotive
Worked as a Software Engineering Intern for various computer vision projects testing and deploying models using Python and C++.
• Achieved a 50% performance improvement by optimizing Yolov5 and Resnet34 deep learning models for Dirty Lens Detection (DLD) and Pedestrian Detection (PD). • Deployed a Convolutional Neural Network (CNN) Semantic Segmentation model, classifying 21 distinct classes in both C++ and Python environments, showcasing proficiency in ML frameworks. • Annotated approximately 10,000 images, carefully labeling objects, and generated new annotated images using the Albumentations library from Python to enhance model performance. • Reviewed and validated annotations using CVAT and Voxel51 for accuracy and consistency, ensuring high-quality training data for machine learning models and contributing to a 15% increase in model precision. • Collaborated on computer vision projects for 3+ renowned automotive manufacturers, including Mazda, Toyota, and Fisker, contributing to innovative solutions in the automotive industry. • Engineered a streamlined Key Performance Indicator (KPI) tool, replacing a labor-intensive manual process; reduced assessment time from hours to a single click, leading to an impressive 80% boost in productivity and efficiency. • Pioneered a novel data preprocessing pipeline, integrating data augmentation techniques and outlier detection methods, resulting in 20% increase in model generalization and robustness.--

McMaster University 09/2019 - 04/2024
, , United States
Degree: Bachelor's Degree
Major:Computer Engineering
Completed my undergraduate degree in Computer Engineering.

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SnigdhaM