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Jenish Upadhyay

@jenishupadhyay

I build fraud detection, anomaly detection, and demand forecasting systems using production-oriented machine learning workflows.

India

Message

What I'm looking for

I'm looking for opportunities to build and deploy machine learning systems, contribute to end-to-end ML workflows, and grow through hands-on work in AI/ML engineering.

I've built and deployed machine learning systems for fraud detection, anomaly detection, and demand forecasting, with hands-on AI/ML engineering experience at Whizent Software Solutions.

At Whizent, I extended fraud and anomaly detection systems with a deep autoencoder, modularized ML pipelines, and deployed Streamlit apps for model comparison, real-time scoring, and result export.

My projects include a 1.75M+ record multi-domain fraud detection system, an unsupervised network anomaly detection system, and a drift-aware forecasting pipeline. I also build responsive web applications with Next.js, React, TypeScript, and Node.js.

Experience

Work history, roles, and key accomplishments

AI/ML Developer Intern

Whizent Software Solutions

May 2026 - Jul 2026 (2 months)

Extended fraud and anomaly detection systems by engineering a deep autoencoder for reconstruction-error-based anomaly scoring. Re-architected ML pipelines into modular stages and deployed Streamlit applications for model comparison and real-time scoring.

Python scikit learn TensorFlow Keras Streamlit Anomaly Detection Fraud Detection Feature Engineering Model Evaluation Class Imbalance Threshold Tuning ML Pipelines

Education

Degrees, certifications, and relevant coursework

Pandit Deendayal Energy University

B.Tech., Computer Engineering

2023 -

Grade: 8.13/10

Pursuing a B.Tech. in Computer Engineering with a CGPA of 8.13/10, expected to graduate in 2027.

Coursera

Machine Learning Specialization, Machine Learning

Completed the Machine Learning Specialization covering supervised learning, advanced learning algorithms, and unsupervised learning.

AWS Training & Certification

AWS Machine Learning Engineer – Associate Learning Plan, Machine Learning

Completed the AWS Machine Learning Engineer – Associate Learning Plan, including hands-on labs on data preparation, model training, deployment, monitoring, and MLOps practices.