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I am Muhammad Ahmad Masood, a Software Engineer with 5 years of experience in computer vision and multimedia systems, focused on building real-time, scalable video processing pipelines. I am proficient in C++ and Python, with hands-on experience in deep learning, image processing, and multimedia frameworks for both edge and cloud environments. In my current role at Hazen.ai, I design and implement end-to-end CV pipelines—GStreamer-based timestamp extraction, NxMeta annotation linkage, and Redis-backed real-time analytics—enabling precise frame alignment and scalable processing for traffic surveillance and ANPR.…I am Muhammad Ahmad Masood, a Software Engineer with 5 years of experience in computer vision and multimedia systems, focused on building real-time, scalable video processing pipelines. I am proficient in C++ and Python, with hands-on experience in deep learning, image processing, and multimedia frameworks for both edge and cloud environments. In my current role at Hazen.ai, I design and implement end-to-end CV pipelines—GStreamer-based timestamp extraction, NxMeta annotation linkage, and Redis-backed real-time analytics—enabling precise frame alignment and scalable processing for traffic surveillance and ANPR.

MUHAMMAD AHMAD MASOOD

Developer, AI Engineer, Data Scientist, +5

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I am Muhammad Ahmad Masood, a Software Engineer with 5 years of experience in computer vision and multimedia systems, focused on building real-time, scalable video processing pipelines. I am proficient in C++ and Python, with hands-on experience in deep learning, image processing, and multimedia frameworks for both edge and cloud environments. In my current role at Hazen.ai, I design and implement end-to-end CV pipelines—GStreamer-based timestamp extraction, NxMeta annotation linkage, and Redis-backed real-time analytics—enabling precise frame alignment and scalable processing for traffic surveillance and ANPR.…I am Muhammad Ahmad Masood, a Software Engineer with 5 years of experience in computer vision and multimedia systems, focused on building real-time, scalable video processing pipelines. I am proficient in C++ and Python, with hands-on experience in deep learning, image processing, and multimedia frameworks for both edge and cloud environments. In my current role at Hazen.ai, I design and implement end-to-end CV pipelines—GStreamer-based timestamp extraction, NxMeta annotation linkage, and Redis-backed real-time analytics—enabling precise frame alignment and scalable processing for traffic surveillance and ANPR.

Available to hire

I am Muhammad Ahmad Masood, a Software Engineer with 5 years of experience in computer vision and multimedia systems, focused on building real-time, scalable video processing pipelines. I am proficient in C++ and Python, with hands-on experience in deep learning, image processing, and multimedia frameworks for both edge and cloud environments.
In my current role at Hazen.ai, I design and implement end-to-end CV pipelines—GStreamer-based timestamp extraction, NxMeta annotation linkage, and Redis-backed real-time analytics—enabling precise frame alignment and scalable processing for traffic surveillance and ANPR.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

Software Engineer at Hazen.ai

September 1, 2024 - Present

Implemented pioneering representation learning and OOD domain generalization techniques, eliminating the need for data annotation, accelerating deep learning training, and cutting costs by 30%. Delivered a high-accuracy ANPR system within 2 months, processing over 4 million vehicles daily, meeting aggressive client timelines. Worked on deep learning architectures for keypoints, object detection, and tracking for vehicle violations. Engineered GStreamer workflows for precise frame alignment from ONVIF video streams. Managed annotated bounding boxes using NxMeta formats and synchronized data using Redis for real-time analytics. Employed advanced computer vision models such as YOLO for real-time vehicle detection and developed analytics modules for vehicle density and speed estimation.

Associate Software Engineer at Devsinc

August 31, 2024 - July 21, 2025

Developed and deployed deep learning models using PyTorch for real-time object detection and tracking in traffic surveillance systems, optimizing inference pipelines for edge devices. Applied machine learning and optimization techniques to improve model accuracy and runtime, achieving a 35% reduction in false positives in city-scale deployments.

Associate Software Engineer at Contour Software

April 30, 2024 - July 21, 2025

Developed monocular depth estimation pipelines for low-light surveillance using self-supervised learning and transformer backbones, improving depth accuracy by 32%. Built multi-view 3D reconstruction systems for vehicle trajectory analysis achieving less than 5cm positional error on custom datasets. Designed lightweight pose estimation models for non-rigid objects optimized for Jetson Xavier, achieving real-time 30 FPS inference.

Associate Software Engineer at Contour Software

June 1, 2023 - April 30, 2024

Improved backend performance by 50% using asynchronous programming, caching, and SQL optimization in distributed systems. Developed and integrated RESTful APIs using Python and C#, enabling scalable service communication. Implemented concurrent solutions for IO-bound and CPU-bound workloads, improving system throughput and responsiveness. Containerized services with Docker and deployed via Kubernetes, ensuring scalability and reliability. Built CI/CD pipelines and monitoring systems, reducing deployment time by 30% and improving production stability.

Freelancer at Fiverr

May 31, 2023 - July 21, 2025

Built and deployed over 7 machine learning applications spanning NLP and computer vision, including custom LLM fine-tuning and real-time video analytics tools, attracting 3,000+ monthly users on demos. Fine-tuned LLaMA 2 and Falcon models for domain-specific text generation tasks with BLEU score improvements of 18% and 50% faster inference by quantization and LoRA. Designed zero-shot classification pipelines for small-sample CV datasets using CLIP and ViT backbones, improving few-shot accuracy by 24%.

Freelance Software Engineer at Upwork

September 1, 2021 - May 31, 2023

Designed and deployed end-to-end computer vision systems using Python, PyTorch, and OpenCV, building scalable backend pipelines for real-time inference on video streams and image datasets. Developed high-performance inference services integrating REST/gRPC APIs, enabling seamless interaction between CV models and downstream analytics systems in production environments. Optimized deep learning models for edge and GPU deployment using NVIDIA TensorRT, applying quantization (INT8/FP16) and structured pruning techniques to achieve up to 2–4× latency reduction while maintaining model accuracy.

Machine Learning Intern at RiseTech.ai

August 31, 2021 - July 21, 2025

Gathered and preprocessed over 10,000 high resolution retinal images with data augmentation reducing overfitting by 25%. Developed and fine-tuned a VGG16-based CNN achieving 92% accuracy and AUC of 0.95 in differentiating exudates and hemorrhages.