AI Engineer with 3+ years of experience architecting end-to-end Generative AI platforms, multimodal pipelines, and deep learning systems. Passionate about translating complex narrative logic and data into production-grade AI-native software.
| Project | Tech Stack | Highlights |
|---|---|---|
| CineSync OS | Claude 3.5 Sonnet · Wan2.2 Diffusion · FastAPI · Next.js 15 · React 19 · TypeScript |
AI Director Operating System that turns screenplays into multi-shot scene coverage. Features client-side BYOK key management, lens focal control (24mm–85mm), and character consistency locks. Live Demo |
| Crop Yield Deep Learning Framework | Python · PyTorch · CNN-RNN Hybrid · LightGBM · Weighted Ensembles |
Deep Learning & Ensemble Modeling Architecture designed for multi-variable agricultural yield prediction. Implemented hybrid temporal-spatial neural networks and custom loss weighting. |
- GenAI & LLM Orchestration: Claude 3.5 Sonnet, OpenAI API, Wan2.2 Video Diffusion, Structured JSON Outputs, Prompt Compilation, In-Browser BYOK Security.
- Full-Stack Engineering: FastAPI, Python, Next.js 15 (Pages/App), React 19, TypeScript, Tailwind CSS, Framer Motion, REST APIs.
- Machine Learning & Core: PyTorch, CNN-RNN Architectures, Ensemble Methods, LightGBM, Scikit-Learn, Pandas, NumPy.
- DevOps & Cloud: Vercel, Render, Docker, Git, Linux, Webhooks & Automation.
- Live Demo: cinesync-os.vercel.app
- LinkedIn: linkedin.com/in/sailesh_krishnan
- GitHub: @SAIELESH