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Anurag Tiwari

@anuragtiwari2

Deep learning-focused AI engineer building production-ready ML systems.

India
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What I'm looking for

I seek hands-on AI/ML roles where I can deliver end-to-end solutions, emphasize model explainability, deploy scalable systems, and work in collaborative teams focused on impactful products.

I am a deep learning-focused AI engineer with hands-on experience building production-grade machine learning systems, from data pipelines to deployment. I specialize in medical imaging, resume screening, and customer churn prediction using Python and modern ML frameworks.

My projects include a CNN-based medical image analysis system deployed on Vultr Cloud that achieved 89% test accuracy and reduced diagnosis time, a GenAI resume rewriter using a locally hosted LLaMA-3 for privacy-preserving ATS optimization, and a churn prediction platform with XGBoost and SHAP delivering >85% ROC‑AUC.

I emphasize end-to-end delivery: data engineering, model training, explainability, API serving, containerized deployment, and performance optimization. I pursue roles where I can apply deep learning and MLOps practices to build impactful, reliable AI products.

Experience

Work history, roles, and key accomplishments

PP
Current

AI Engineer

Personal Projects

Sep 2024 - Present (1 year 9 months)

Designed and deployed multiple AI systems including a CNN-based medical image analysis achieving 89% accuracy and real-time inference <500ms, a semantic resume screening and GenAI rewriter, and a customer churn prediction platform with >85% ROC-AUC.

Education

Degrees, certifications, and relevant coursework

NT

Noida Institute of Engineering and Technology

Bachelor of Technology, Computer Science Engineering

2022 -

Activities and societies: Completed AI and deep learning projects including medical image analysis, resume screening GenAI, and customer churn prediction; earned IBM and Infosys certificates.

Pursuing a Bachelor of Technology in Computer Science Engineering with coursework and projects focused on machine learning, deep learning, and full-stack AI systems.

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