AI & Machine Learning Engineer | Generative AI | LLMs | AI Agents | Automation
📍 Pakistan | 💼 Freelance | 💲 $35/hr

I am an AI & Machine Learning Engineer with a strong focus on designing and building production-ready AI systems. My work emphasizes reliability, scalability, and real-world usability rather than experimental prototypes.

I specialize in Generative AI, Machine Learning, AI Agents, and automation pipelines, helping startups and organizations transform ideas into deployable, maintainable, and scalable AI products.

Rather than simply integrating APIs, I design end-to-end AI architectures that include data pipelines, models, agents, APIs, and deployment workflows, with careful attention to performance, security, and long-term maintainability.

• Machine Learning and Deep Learning model development
• Supervised and unsupervised learning (classification, regression, clustering)
• Natural Language Processing (NLP) pipelines and semantic search
• Model training, evaluation, optimization, and deployment

• LLM-powered applications using proprietary and open-source models
• Retrieval-Augmented Generation (RAG) using LangChain and LlamaIndex
• Vector databases: Pinecone, FAISS, ChromaDB, Qdrant, Weaviate
• Prompt engineering (zero-shot, few-shot, multi-turn)
• Fine-tuning techniques: LoRA, QLoRA, PEFT, RLHF, DPO
• Embeddings, document ingestion, and knowledge-base systems

• AI agent development using CrewAI, AutoGen, and LangChain Agents
• Multi-agent workflows and task orchestration
• Conversational AI and domain-specific chatbots
• Voice AI integrations (speech-to-text and text-to-speech)
• Workflow automation using n8n and event-driven pipelines

• Python backend development: FastAPI, Flask, Django
• RESTful API design and secure microservices
• Frontend integration with React and Next.js
• Databases: MongoDB, PostgreSQL, MySQL, Firebase

• Cloud platforms: AWS, Azure, Google Cloud Platform
• Model deployment: AWS SageMaker, RunPod, GCP AI Platform
• Dockerized applications and Kubernetes orchestration
• CI/CD pipelines for AI systems
• Inference optimization: vLLM, TGI, TensorRT-LLM
• Model quantization: AWQ, GPTQ, GGUF, GGML

• Data pipelines using Airflow, PySpark, and Databricks
• Data preprocessing and synthetic data generation
• Model monitoring, evaluation, and lifecycle management

• Architecture-first system design
• Emphasis on scalability and maintainability
• Clear documentation for long-term ownership
• Focus on business impact alongside technical excellence

• Machine Learning & Deep Learning
• Python, TensorFlow, PyTorch, Scikit-Learn
• Natural Language Processing
• Generative AI & Prompt Engineering
• Data Analytics & Visualization
• Model Deployment & MLOps

I collaborate closely with clients and teams to deliver AI solutions that are robust, scalable, and production-ready.

Contact Information

• Email: adnanarshad0127@gmail.com
• WhatsApp: +92 322 5807361

Availability: 7 days a week
Communication: Clear, timely, and transparent