My freelancing services focus on delivering end-to-end, production-ready AI systems with a specialization in Generative AI and scalable cloud operations.
Generative AI & Model Optimization
Custom GenAI Solution Design: Architect and deploy advanced Retrieval-Augmented Generation (RAG) pipelines leveraging LLMs (GPT, LLaMA) and vector databases (Chroma, Weaviate) for multi-format content processing (documents, images, video, SQL).
AI Model Optimization: Apply state-of-the-art techniques like LoRA/PEFT finetuning and 8-bit quantization to significantly boost model performance, reduce latency, and ensure cost-effective inference.
Systematic Quality Assurance: Design and implement comprehensive evaluation frameworks (e.g., WER, MOS, latency, throughput) to ensure model quality and optimize for business cost efficiency.
MLOps & Cloud Infrastructure
Scalable Cloud Deployment: Build and manage highly available, secure, and cost-optimized cloud-native MLOps infrastructure on Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE).
CI/CD Automation: Implement robust Docker-based CI/CD workflows for continuous training, deployment, and monitoring of AI models.
Performance Monitoring: Set up and manage system monitoring using tools like Grafana to ensure uptime and resource allocation align with business goals.
Cost Efficiency: Expertise in optimizing GPU workloads and fine-tuning schedulers, proven to achieve significant resource utilization savings (up to 18%).
Data & Software Engineering Integration
Data Pipeline Architecture: Design reliable, version-controlled training data pipelines integrating large-scale warehousing (BigQuery) and real-time databases (Firestore/NoSQL).
Full-Stack Integration: Develop robust RESTful APIs (Node.js/JavaScript) for seamless AI model integration into production applications.
Automated Testing: Build Python-based automated test frameworks (Pytest, Selenium) and utilize NLP (spaCy) for sophisticated log and system verification, ensuring high test coverage and reliability.