I am a Computer Science and Engineering graduate specializing in Generative AI and applied machine learning. I have hands-on experience across the machine learning lifecycle, including dataset development, diffusion model fine-tuning, LLM integration, and deployment-oriented development.
I work primarily with Python and PyTorch to build deep learning solutions involving CNNs, RNNs, GRUs, diffusion models, LoRA, SDXL, and InstructPix2Pix. My AI experience also includes prompt engineering, retrieval-augmented generation, and GPT-4o-mini integration.
I also bring full-stack development skills using React.js, Next.js, Node.js, TypeScript, JavaScript, Django, MongoDB, and RESTful APIs. I enjoy translating AI capabilities into usable, scalable web applications.
In my Frontend AI Engineer internship, I reviewed AI-generated user interfaces, improved their production quality, analyzed LLM token costs, and evaluated accessibility and performance. I have experience deploying applications with Vercel and working with AWS services.
My academic and project work includes a multi-instruction image editing system, an EEG brain-to-image interface, and a full-stack gym membership platform. I am seeking an Applied AI or Generative AI Engineer role where I can build and ship LLM-powered and generative systems at scale.
