Professional Overview
AI/ML Engineer with 2 years of hands on experience building and shipping production AI systems. My work covers LLM fine tuning, Speech AI, RAG pipelines, agentic workflows and cloud deployment. I have trained and deployed 4 live models and currently working full time in AI while doing my MS in Computer Science from FAST University.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Fine-tuned Whisper Large-v3 on 1.5M+ audio samples using LoRA for production ASR
- Deployed 4 live AI models on Modal Cloud with autoscaling and sub second latenc
- Built RAG pipeline using FAISS, HuggingFace embeddings and LLaMA 3 from scratch.
- Building fraud detection system with ML models, GNN and rule engine for banking.
- Promoted to AI/ML Engineer owned full ML lifecycle from data to live deploymen
Key Achievements / KPIs
- Dari STT: 12.29% WER. Pashto STT: 0.7s/request after int8 quantization.
- Trained VITS2 TTS from scratch on 41K clips — deployed at 1.88s warm latency.
- Deployed 4 live STT and TTS models on Modal Cloud across Pashto and Dari.
Education
Field of Study: Artificial Intelligence and Machine Learning
Field of Study: Computer Engineering
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
