Yamuna Sugumar

Computer Vision Engineer with 3+ years of experience across computer vision, AI-driven image processing, Python, C++, OpenCV and CUDA, building high-performance solutions for automotive and industrial applications. Proven expertise in image registration, defect detection, GPU optimization, deep learning and real-time vision systems with measurable improvements in accuracy, latency and inspection speed. Brings strong problem-solving and software engineering skills to develop reliable, scalable computer vision solutions that improve perception, automation and production performance.

Computer Vision Engineer - General Motors - Canada

(2025-04)

• Developed computer vision software using Python and C++ to process visual data for automotive perception applications, building reliable production-oriented components that supported real-time engineering and advanced vehicle technology initiatives.
• Implemented AI-driven vision workflows using deep-learning techniques for visual data analysis and perception tasks, converting image inputs into actionable model outputs for evaluation and iterative improvement by computer vision engineering teams.
• Optimized image-processing pipelines for latency-sensitive computer vision workloads, improving computational efficiency and supporting the responsiveness required by real-time automotive perception systems.
• Evaluated computer vision model performance through systematic testing, debugging and failure analysis, identifying challenging visual scenarios and translating findings into improvements in model robustness and overall system reliability.
• Integrated vision algorithms into software workflows using C++, Python and Git, supporting collaborative development and iterative deployment across cross-functional engineering teams during 16+ months of automotive software development.
• Contributed to AI and computer vision initiatives by translating image-processing and machine-learning concepts into scalable software components, supporting reliable perception capabilities for automotive applications and production-oriented engineering workflows.

Software Engineer (Computer Vision) - Yantravision Software Pvt. Ltd. - India

(2021-05 - 2023-03)

• Designed OpenCV-based image-registration algorithms for automated industrial inspection, improving registration accuracy to 98% and enabling consistent image alignment and print quality across production workflows.
• Built end-to-end computer vision tools using Python and C++ for image alignment, defect detection, localization and image augmentation, automating inspection processes and improving the reliability of print-quality analysis.
• Engineered high-efficiency CUDA kernels for computationally intensive image-processing operations, reducing processing latency from 50+ ms to 19 ms and enabling the inspection system to meet real-time performance requirements.
• Profiled GPU workloads using NVIDIA Nsight and NVIDIA Visual Profiler, identifying processing bottlenecks and optimizing execution paths to improve performance across high-throughput computer vision pipelines.
• Streamlined automated inspection workflows by optimizing image-processing stages and execution efficiency, increasing inspection speed by 45% while improving system reliability and minimizing operational downtime.
• Delivered scalable computer vision solutions covering image registration, defect detection and localization, translating vision algorithms into production-ready inspection capabilities for industrial manufacturing applications.

Ontario Graduate Certificate - Analytics in Business Decision-Making - George Brown College (2024-05 - 2024-12)

Ontario Graduate Certificate - Artificial Intelligence in Design and Implementation - Georgian College (2023-05 - 2023-12)

Bachelor - Electrical & Electronics Engineering - PSG Institute of Technology and Applied Research (2017-08 - 2021-03)