Tayyab A.

From idea to production — I build AI systems that actually deliver in real-world environments. I’m an AI Engineer with over 10 years of experience designing, developing, and deploying scalable AI solutions. I specialize in building production-ready, reliable AI systems with strong evaluation, monitoring, and hallucination control. I have done project like shoplifting, dispatching agents, context understanding etc. I’ve worked with startups and enterprises across USA, UK, Canada, Germany, UAE, and Saudi Arabia. 🔥 What I Can Do For You ✔ End-to-end AI systems (research → development → deployment) ✔ Develop Computer Vision, NLP, and Deep Learning solutions ✔ Design Generative AI and multi-agent (Agentic AI) systems ✔ Build advanced RAG pipelines (hybrid, graph-based, and vectorless retrieval) ✔ Optimize and deploy models for cloud, edge, and real-time streaming systems ✔ Develop scalable APIs, microservices, and backend infrastructure ✔ Implement MLOps pipelines with CI/CD, monitoring, and evaluation 🧠 Core Expertise ➜ Languages: Python, C++, C, TypeScript, and Java ➜ AI domains: Machine Learning, Deep Learning, Agentic AI, Generative AI, Computer Vision, NLP, and Multimodal AI ➜ Agentic AI frameworks: LangChain, LangGraph, CrewAI, LlamaIndex, and OpenAI and Claude APIs ➜ Computer Vision frameworks: PyTorch, TensorFlow, OpenCV, Ultralytics, and Hugging Face ➜ Agentic AI skills: LLM apps, RAG, agent orchestration, tool calling, and context engineering ➜ Computer Vision skills: image and video processing, real-time inference, and edge optimization ➜ Model training, fine-tuning (LoRA, QLoRA), evaluation, and data annotation ➜ AI solution architecture, system design, and technical consulting Frameworks & Libraries: PyTorch, TensorFlow, OpenCV, Transformers, HuggingFace LangChain, LangGraph, LlamaIndex, Ollama Computer Vision Models & Techniques: Detection: YOLO, Faster R-CNN, SSD Classification: ResNet, EfficientNet, Vision Transformers (ViT) Segmentation: U-Net, Mask R-CNN, DeepLab Pose Estimation: YOLO, MediaPipe, OpenPose Generative Vision: GANs, VAEs, Diffusion Models Video & Tracking: DeepSORT, Optical Flow, Anomaly Detection Monitoring and Evaluation: Weights & Biases, MLflow Custom model training, fine-tuning, and optimization for real-time and edge deployment 🤖Generative and Agentic AI Systems: LLM APIs: OpenAI (GPT), Google (Gemini), Antropic (Claude) Local LLMs: Llama, Mistral, DeepSeek, Qwen, Gemma LLM Fine-tuning: LoRA / QloRA RAG: Graph RAG, Agentic RAG, long-context optimization, context compression Retrieval: Hybrid Search (BM25 + vector), Re-ranking (cross-encoders) Vector DBs: FAISS, Pinecone, Weaviate, Milvus, Qdrant, ChromaDB Vectorless: Keyword-based indexing (BM25), PageIndex-style retrieval LLM Evaluation and Monitoring: RAGAS, DeepEval, LangSmith Docling: document ingestion, parsing, and structuring for RAG pipelines LLM hallucination mitigation & reliability ⚡Edge AI: NVIDIA Jetson (Nano / Orin), Raspberry Pi, Hailo RTSP, WebRTC Multi-video processing using DeepStream Inference optimization using TensorRT, ONNX Runtime, and Hailo toolchains Quantization (INT8/FP16), pruning, and graph optimizations 🛢️ Databases: MongoDB, PostgreSQL, MySQL ☁️ Cloud, MLOps & Infrastructure: AWS (Lambda, EC2, SageMaker, S3, ECR, ECS, Fargate, Bedrock) GCP (Vertex AI, AI Studio) Docker MLflow, Airflow, DVC CI/CD: GitHub Actions, Jenkins, AWS CodePipeline 🏆 Why Clients Work With Me ✔ 8+ years of hands-on experience (Python, C/C++) ✔ 100+ Projects Completed ✔ Production-first mindset (not just prototypes) ✔ Strong focus on reliability, evaluation & scalability ✔ Clean, maintainable architecture & best practices ✔ Clear communication & consistent updates ✔ Long-term support and system ownership 💡 My Approach I don’t just build AI features, I design robust, scalable, and trustworthy AI systems. From early-stage prototypes to production-grade systems, including real-time computer vision, advanced RAG pipelines, and multi-agent architectures. Let’s build something powerful 🔥.