Zaraar Malik

As an AI/ML Engineer, I have designed and implemented intelligent solutions across NLP, Computer Vision, and Generative AI. My industry experience includes building a Retrieval-Augmented Generation (RAG) chatbot to enhance customer support, fine-tuning BERT for entity extraction in customer reviews, and creating multilingual dubbing systems using Whisper, TTS, and Wav2Lip for realistic speech-to-video sync.

My project portfolio reflects end-to-end system development. I led the creation of Snap Shop, a web platform enabling users to visualize themselves in selected garments using diffusion models and LoRA fine-tuning. Other notable projects include procedural game level generation using GANs, automated hidden object detection using YOLO and Faster R-CNN, and multi-modal meme sentiment analysis by fusing vision and language inputs.

I’m proficient in Python, C++, JavaScript, and tools like PyTorch, FastAPI, Flask, Docker, and Kubernetes. My technical expertise spans across CNNs, LSTMs, Transformers, YOLO, SAM, RAG, and Diffusion Models. I've been recognized in national hackathons, securing top positions in AI competitions such as Data Quest at Nascon and the AIO Hackathon, and have consistently demonstrated excellence through both technical innovation and impactful results.