Hi, I'm Manish Tiwari, a final-year Computer Science student at IK Gujral Punjab Technical University, Punjab.
I build practical machine learning systems and enjoy taking ideas from experimentation to deployment. My interests lie in MLOps, AI systems, LLM applications, and the engineering required to make machine learning useful in real-world environments.
Along the way, I've trained small language models, built production-oriented ML applications, contributed to open source, and explored how reliable AI systems are designed and maintained.
More about me
My journey into machine learning started with curiosity about how computers learn from data. Over time, that curiosity expanded beyond model training into the broader challenges surrounding machine learning systems: data pipelines, deployment, monitoring, reliability, and scalability.
I enjoy learning by building. Most of my projects are end-to-end implementations where I can explore the complete lifecycle of a system rather than a single component. This approach has helped me understand both the technical and practical aspects of turning ideas into usable products.
Open source has been an important part of my growth as an engineer. Contributing to projects such as Huggingface, Augur, Shap, moss, and other community-driven repositories has exposed me to collaborative development, code reviews, and the standards required to build software used by real communities.
Beyond engineering, I enjoy writing about technology, research culture, and the evolving AI ecosystem. Writing helps me organize my thoughts and better understand the ideas I'm exploring.
Outside of technology, I spend time in the gym, enjoy long cycling trips, and take walks that often become brainstorming sessions for future projects and ideas.
Journey
2023 — Started building ML and data science projects.
2024 — Explored software engineering and networking projects.
2025 — Focused on machine learning, open source, and technical writing.
2026 — Building AI systems, MLOps tools, and LLM-based applications.
2027 — Nobody knows!