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Computer Vision Engineer with 3+ years in Deep Learning & Edge AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven AI & Computer Vision Engineer with a proven track record of designing, optimizing, and deploying production-grade machine perception and generative AI systems. Specialized in developing high-performance vision pipelines, leveraging state-of-the-art Vision-Language Models (VLMs), and implementing real-time object tracking, segmentation, and face recognition models. Expert in edge AI acceleration, optimizing complex deep learning models for deployment on resource-constrained platforms (such as Raspberry Pi and NVIDIA Jetson), and building robust API infrastructures.
Iqra University
BS in Computer Science · Computer Science
August 1, 2017 – June 30, 2022
NeuViTechology
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d2Al.ca Inc
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Rapidev
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October 1, 2022 – July 1, 2023
Islamabad, Islamabad Capital Territory, Pakistan
Deep Learning & CV: Object Detection with PyTorch
Unknown
June 1, 2026 – Present
Build with Gemini 3
Unknown
June 1, 2026 – Present
Introduction to Machine Learning with KNIME
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience spans multiple companies and diverse application domains (sports, surveillance, satellite imagery, biometrics, industrial automation), indicating adaptability and a broad interest in applying computer vision. The remote work experience suggests self-discipline and effective communication in distributed environments. The continuous learning through certifications (Deep Learning & CV, Build with Gemini 3) shows a proactive attitude towards staying current with technology, which aligns well with an innovative and growth-oriented culture.
Soft Skills & Operational Fit
The candidate's resume demonstrates strong problem-solving skills through optimizing models for performance and resource constraints. Their experience in leading development and architecting solutions suggests initiative and a structured approach. The diverse project portfolio indicates adaptability and a willingness to tackle varied challenges. The descriptions imply a focus on delivering production-grade, scalable solutions, which is crucial for operational fit in a senior role.