I’m a Data Scientist, Machine Learning & Deep Learning Engineer, and Full-Stack (MEAN) Developer with 2+ years of experience building, fine-tuning, and deploying AI/ML solutions across NLP, Computer Vision, and Generative AI.

• Designing end-to-end ML pipelines — from dataset preparation → training → evaluation → deployment
• Building NLP systems (transformers, LoRA fine-tuning, quantization, efficient inference)
• Computer Vision & OCR solutions optimized for embedded/edge devices
• Generative AI with LLMs (Transformers, Unsloth, Ollama, OSS-120B, LoRA)
• Deployment on cloud & edge (Raspberry Pi, containers, GPUs, RunPod)
• Full-stack MEAN development integrated with AI backends

Languages & Frameworks: Python, JavaScript (Node.js, Angular, Express, MongoDB), PyTorch, TensorFlow, Hugging Face, FastAPI, Flask, LangChain
Specialties: NLP, Computer Vision & OCR, Generative AI, Edge AI (Raspberry Pi, IoT)
Tools & Platforms: Docker, Kubernetes, RunPod, GCP, AWS, Azure, MongoDB, SQL, Pandas, NumPy, GitHub Actions (CI/CD)

• Building scalable transformer-based systems
• Exploring quantization techniques for large models (OSS-120B, LLaMA variants)
• Developing interactive drug pipeline visualizations with target-style JS plots
• Advanced pandas coding challenges & data wrangling

• Optimizing inference pipelines for low-resource GPUs
• Studying drug discovery workflows (MOA clustering, phase visualizations)
• Turning complex ML concepts into production-ready systems

💼 Open to collaborations in AI/ML research, LLM deployment, and data visualization.
🌐 Always exploring forward-thinking AI systems.