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Sarmad Ali
@sarmadali_
Turning Data, Ideas, and Designs into actionable results
Pakistán
Hindi, Inglés, Urdu, Alemán, Francés
Sobre mí
Full Stack Developer and Data Science graduate from FAST NUCES Islamabad with hands-on experience building and deploying end to end web applications. Proficient in React.js, Next.js, FastAPI, and Node.js across the full development lifecycle from database design and REST API architecture to responsive frontend interfaces and production deployment. Comfortable working across the stack with strong experience in real-time systems, authentication, and containerised deployments.
Habilidades
Sarmad Ali
desconectado •
Revisa mis servicios
Procesamiento de lenguaje natural
I will do data science tasks, do nlp, text analysis using python
Deep learning
I will do your deep learning, machine learning and ai projects
Porfolio
Experiencia laboral
Data Science/Analysis Trainer
Training • Tiempo completo
Aug 2026 - Present • 2 mos
-Deliver practical, job-focused training sessions on Data Science, Machine Learning, and Data Analysis to students as part of Future Connect's Digital academy. - Teach Python (Pandas, NumPy, Scikit-learn), SQL, Power BI, Tableau, and ML fundamentals; guide students through hands-on projects covering EDA, model building, and data visualisation. - Support students with CV preparation, mock interviews, and career guidance to improve employability outcomes in data and AI roles.
Full Stack Media Engineer
Speeqr • Tiempo completo
May 2026 - Aug 2026 • 3 mos
- Debug audio sync issues across multi-room conferencing using NTP/GCC-PHAT alignment, fix a 16kHz/48kHz sample rate mismatch causing buffer overflow. - Implement an adaptive jitter buffer and reduce end-to-end audio latency from 3-4 seconds to under 1 second through buffer tuning and AudioContext optimisation. - Research WebSocket, WebRTC, and WebTransport/QUIC tradeoffs to inform architecture decisions on a .NET 9/C# + WebRTC stack; access and test deployments on AWS EC2 instances via RDP.
AI Automation Engineer
LinkedIn • Tiempo completo
May 2025 - Aug 2025 • 3 mos
Designed LLM-based automation pipelines to eliminate repetitive operational tasks; integrated language model APIs with internal tooling to enable intelligent, context-aware process automation.
