
AI Engineer with 2+ years in Machine Learning, Deep Learning, and Generative AI
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Results-driven AI Engineer with 1.5+ years of experience building AI-driven systems, agentic workflows, and LLM-powered applications. Proficient in machine learning, deep learning, and Generative AI with hands-on expertise in deploying LLMs, designing RAG pipelines, and scalable backend development. Adept at bridging MLOps and software engineering to deliver production-ready AI solutions.
Bahria University
BS Software Engineering · Software Engineering
August 1, 2022 – June 30, 2026
Clinet Pvt Ltd
AI/ML Engineer (Contract)
January 1, 2025 – December 31, 2025
India
Independent
AI/ML Tutor
January 1, 2024 – Present
India
Digital Empowerment Network Pakistan
ML Intern
January 1, 2024 – December 31, 2024
India
Accelerating Image Classification with GPUs
January 1, 2023 – January 1, 2024
Accelerated CIFAR-10 training from 1,882s to 358s (5.25x speedup) and reduced inference time from 6.10s to 2.17s (2.81x faster) using GPU-optimized deep learning workflows. Improved image classification accuracy from 70.04% to 73.21% (+3.17%) through parallel computing architecture, demonstrating significant gains over traditional CPU-based processing.
Sentimo - Sentiment Analysis System
January 1, 2023 – January 1, 2025
Built a real-time sentiment pipeline using DistilBERT and PyTorch, delivering predictions in <500ms across 4 languages with Google Translate API integration. Deployed a full-stack Flask app with dynamic sentiment UI, reducing computational overhead by ~40% via DistilBERT's distilled architecture without sacrificing accuracy.
Oraculum - AI-Based Financial Advisor
January 1, 2023 – June 1, 2026
Built a modular AI-powered financial advisor using FastAPI, Docker, and microservices with 5+ backend services covering transaction management, spending insights, and real-time crypto tracking. Developed a Stacked LSTM stock model (1.67% avg error) and RAG-based chatbot delivering personalized financial advice across a user's full portfolio.
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from academic research to personal projects and contract work, indicates a proactive and self-driven individual. The tutoring role suggests a willingness to share knowledge and contribute to a learning environment. The breadth of technologies and problem domains tackled (image classification, sentiment analysis, financial advice, LLM deployment) demonstrates adaptability and a strong interest in various aspects of AI engineering, aligning well with an innovative and fast-paced AI team.
Soft Skills & Operational Fit
The candidate's experience as an AI/ML Tutor suggests strong communication and mentoring skills, which are valuable for team collaboration and knowledge sharing. Project descriptions indicate an ability to work on complex, multi-component systems, implying good problem-solving and organizational skills. The focus on performance optimization (GPU acceleration, DistilBERT for efficiency) shows an operational mindset towards delivering practical solutions.