About

The through-line has been the same question in different clothes: how do you know the model is right. At Samsung it was image restoration you could judge by eye. At Michelin it is a natural-language interface to a pricing warehouse, where the answer looks equally plausible whether or not it is correct, and eyeballing it stops working.

That is why most of what I build now is evaluation and guardrails rather than models. Benchmarks that exist before the system does, read-only enforcement that holds at every layer, gates that stop the agent when it is uncertain instead of letting it guess confidently.

I am in Pune, India, and I am looking for work where the system has to hold up under real users rather than a demo.

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Positions

Mar 2026 — PresentAssociate Data Scientist
Michelin
Jun 2024 — Mar 2026Assistant Data Scientist
Michelin
Jun 2023 — May 2024AI Research Intern
Michelin
Feb 2023 — Jun 2023Research Intern — Samsung PRISM
Samsung R&D Institute India
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Education

Sep 2020 — Jun 2024SRM Institute of Science and Technology
B.Tech, Computer Science (Big Data Analytics), GPA 9.25 / 10
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Skills

Generative & Agentic AI: LangGraphLangChainReAct agentsMulti-agent systemsMCPRAGPrompt engineeringFine-tuning (LoRA, QLoRA)

Machine Learning & NLP: PythonPyTorchTensorFlowTransformersLLMsModel evaluationAnomaly detectionForecasting

ML Engineering: Azure MLMLflowDockerKubernetesCI/CDREST APIsSQLDremioReactTypeScript