About
Hi reader, welcome to my space. I am a IIT Kharagpur graduate in Electrical and Electronics engineering. I have listed my projects at https://www.neatcraft.ai/. You can visit for a better look at my work and projects. I am a seasoned AI engineer and a data scientist. I work on LLMs, Agentic AI, RAG. I like to work on large-scale datasets and extract meaningful business insights. My projects and experience range from using classical machine learning models, deep learning to transformers involving applications of large-language models. I have experience of using cloud especially Azure, creating API endpoints, dockerizing it for bridging the gap between making ML models and deployment for end-use. I am an avid reader about latest AI technologies and frameworks but I also implement this theory in my day-to-day workings to make the output efficient and effective. I blog at github to share my learnings and keep alive the practice of writing. I also believe in the saying "You should write to know what you are thinking". Link to my writings: https://github.com/mukeshbarnwal I would be happy to collaborate to share about my learnings and insights and learn from each other. You can reach out to me at mukeshbarnwal.iit@gmail.com Thank you for reading.
Work experience
Artificial Intelligence Engineer at Tata Consultancy Services, Jun 2026 - Present · 3 mos, Bengaluru, Karnataka, India
AI Engineer at Synkcode, Sep 2025 - May 2026 · 9 mos, Handled the lifecycle of AI product from building to demployment
Data Scientist at Kenvue, Jul 2024 - Sep 2025 · 1 yr 3 mos, Worked on multiple Generative AI projects involving fine-tuning, prompt-engineering with use-cases involving document classification, complaint categorisation. Tools and languages used: Large language models, Azure, Python, ChromaDB
Career transition at Career Break, 2021 - 2023 · 2 yrs, U.P.S.C. Civil Services Examination, Ranked in the top 0.5% among 500,000+ candidates, advancing to the Final Interview stage in 2023
Data Analyst at Captain Fresh, Dec 2020 - Jun 2021 · 7 mos, On-site
