Zain Ul Abdin

Generative AI Engineer

Freelance AI Engineer • Freelance

Feb 2020 - Present • 6 yrs 3 mos

⭐️ 1830+ hours on Upwork ⭐️ 56+ projects delivered ⭐️ 6+ years of experience ⭐️ Specializing in Delivering High-Value, Enterprise-Grade Projects As an AI Engineer with deep expertise in machine learning, deep learning, generative AI, and LLMs, I help startups and enterprises automate complex tasks, optimize operations, and unlock new revenue streams through production-grade AI systems. I design and deploy intelligent systems that go beyond prototypes, automating complex workflows, cutting costs, and enabling growth across industries. With deep expertise in Machine Learning, Deep Learning, Generative AI, LLMs and RAG, I help businesses build real-world solutions that scale. I've delivered impactful solutions across healthcare, edtech, and SaaS, helping clients build intelligent systems that integrate text, images, documents, and custom knowledge bases. My work includes fine-tuning open-source LLMs (GPT-4, Claude, LLaMA, Mistral), building LangChain-based agents, and engineering multimodal RAG pipelines to automate workflows. 🔧 Key Contributions & Results: ✅ Reduced manual document analysis by 70% with custom RAG pipelines ✅ Cut token costs by 75% while maintaining 99.9% uptime in deployed LLM apps ✅ Delivered AI recommendation system unlocking $500K+ in new revenue ✅ Improved semantic search by 30%+ using advanced embeddings and FAISS ✅ Deployed automated CI/CD pipelines for ML/LLMs, cutting model iteration time by 60% ✅ Fine-tuned open-source models to achieve 3× improvement in task accuracy I specialise in end-to-end ML/LLM systems, from data engineering and model training to MLOps/LLMOps infrastructure using MLflow, Airflow, Hugging Face, DVC, and more. My deployments are cloud-native, GPU/CPU optimized, and built for performance at scale. Clients hire me to deliver results, not just experiments. If you're looking for an AI expert who speaks both code and business,

Machine Learning Engineer

Consforc Lahore Pakistan • Full time

Dec 2014 - Oct 2019 • 4 yrs 10 mos

As a Machine Learning Engineer at ConsForc, I designed, developed, and deployed data-driven solutions using classical machine learning and early deep learning techniques. My work spanned multiple industries, including healthcare, legal tech, and retail, where I built predictive models and automated analytical workflows that enabled organizations to make faster, more accurate, and cost-effective business decisions. Collaborating with cross-functional teams, I delivered production-ready ML systems that translated complex datasets into actionable insights. Key Responsibilities: ✅ Designed and implemented end-to-end machine learning pipelines, covering data preprocessing, feature engineering, model training, validation, and deployment. ✅ Applied statistical modeling and classical ML techniques (regression, classification, clustering, SVMs, random forests) to solve business-critical problems. ✅ Developed and optimized deep learning architectures (CNNs, RNNs, LSTMs, GRUs) for image recognition, time series forecasting, and sequential data modeling. ✅ Partnered with product managers, domain experts, and engineers to align ML solutions with strategic business objectives. ✅ Implemented scalable deployment strategies for ML models, ensuring reliability and consistent performance in production environments. Key Achievements: ✅ Boosted fraud detection accuracy by 24%, reducing false positives and saving $1.2M annually. ✅ Delivered CNN-based imaging model with 96% accuracy, cutting radiology review time by 40%. ✅ Improved demand forecasting accuracy by 21%, lowering stockouts by 18% for a retail client. ✅ Automated patient screening pipeline, reducing processing time by 65% while maintaining >93% sensitivity. ✅ Delivered ML solutions adopted by 7 enterprise clients, contributing to multi-year contracts and repeat engagements