Fariha Muazzam
I build production-ready AI systems that actually ship
Ready for work
Fariha is ready for their next project!
Satellite imagery is the ultimate stress test for Computer Vision.
It is not just about detection; it is about architecting precision across massive, high-resolution datasets where every pixel counts.
I have been building AI pipeline to segment parking lots, walkways, and structures from aerial data. The challenge is not just the mode, it is the Infrastructure:
- Tiling & Inference: Processing massive dimensions without losing small-object context.
- Robust Pre-processing: Using OpenCV to handle varying lighting and atmospheric "noise."
- Cloud Orchestration: Turning heavy segmentation models into responsive, scale-ready tools.
It is about turning raw pixels into a reliable data layer for the business.
Currently opening 20 hours/week for long-term partnerships in Computer Vision & AI Systems.
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AI-based Video Generation Pipeline
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I designed and delivered an end-to-end MVP for a real-time AI talking avatar system, where live browser speech is converted into an AI-generated response and rendered through a lip-synced avatar video on GPU hardware.
The objective was to validate technical feasibility, latency characteristics, and perceived real-time interaction before committing to production hardening. The system integrates speech-to-text, LLM-based reasoning, text-to-speech, and video synthesis into a single, runnable pipeline, deployed on an A100 GPU.
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At Formulatrix, I led the development of a computer vision pipeline for RockMaker, a biotech product used in crystallization experiments. I built and deployed object detection and image classification models that improved scoring accuracy by 13%, reducing manual effort for scientists and increasing customer satisfaction. The solution was productionized with Docker and CI/CD pipelines, ensuring scalability and reliability across client sites.
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