Experience:
Computer Vision Engineer — Glueck Technologies Jan 2025 – Dec 2025
- Deployed GPU-accelerated computer vision pipelines processing thousands of daily inferences.
- Improved inference latency by 38% using Nvidia DeepStream and GPU profiling techniques.
- Maintained 99.5% uptime through robust deployment and monitoring practices.
- Worked closely with infrastructure teams to optimize edge and cloud deployments.
- Implemented video preprocessing pipelines (resize, normalization, batching) to stabilize real-time
inference.
- Tuned confidence thresholds and post-processing logic to reduce false positives in production streams.
- Integrated logging and metrics to track FPS, GPU utilization, and error rates.
- Debugged model performance degradation caused by lighting, angle, and motion variance.
- Assisted in camera calibration and stream quality validation for deployment environments.
Software Developer | Taylor's University| Sept 2025 – Jan 2026
-Led full-stack development of centralized web portal serving 5000+ students, faculty, industry partners
-Architected solution reducing internship placement processing time by 40% through automated
workflows
-Designed RBAC system ensuring secure data visibility for students, supervisors, and partners
-Collaborated with academic leadership and industry partners to translate stakeholder needs into technical
-Engineered real-time notification system improving communication efficiency by 60%
-Spearheaded architecture decisions, delivering ahead of schedule with zero critical bugs
Education:
BSc (Hons) Computer Science (Dual Degree) — GPA: 3.6/4.0
Taylor’s University & University of the West of England
Skills:
• Computer Vision: YOLO, FaceNet, OpenCV, video analytics, OCR, Segmentation, Tracking
• GPU & Optimization: Nvidia DeepStream, TensorRT, performance profiling, CUDA, Quantization
• Deployment: Docker, FastAPI, REST APIs, Kubernetes, TorchServe, Edge deployment (Jetson)
• Cloud & Systems: AWS (Sagemaker, EC2), Linux, CI/CD, GCF Terraform, Prometheus/Grafana
• Languages: Python, C++, SQL, PyTorch, TensorFlow, Bash, SQL, Git
Additionally:
Computer Vision Engineer specializing in real-time video analytics and GPU-accelerated inference.
Experienced in deploying vision models to production environments, optimizing FPS, latency, and system
reliability for edge and cloud-based workloads.
