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Deekshant Gupta

@deekshantgupta

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Software engineer intern focused on building reliable systems and AI/ML-powered features.

India

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What I'm looking for

I’m looking for a role where I can build reliable backend systems and apply ML/NLP to real product problems, with strong engineering mentorship and ownership on impactful features.

I’m an SDE Intern who enjoys turning complex workflows into dependable, scalable software. I’ve worked on integrating third-party email connections using Redis and BullMQ, and I’ve focused on performance and reliability for high-volume production workloads.

In my internship work, I integrated email account connections across 5+ platforms and supported 50k+ Google & Microsoft accounts, using Redis and BullMQ to improve performance and reliability. I also revamped a ColdMail Reseller platform by updating legacy mailbox operations, rewriting cron jobs, and migrating backend components to optimized implementations to strengthen code quality and long-term maintainability.

I’m also driven by applied AI and data work, building end-to-end credit risk models and exploring modern NLP/RAG systems. Through projects like MailScheduler, NextFlow, and AskWise, I’ve shipped fault-tolerant scheduling, visual AI workflow orchestration, and context-aware QA pipelines—pairing strong backend engineering with practical machine learning skills.

Experience

Work history, roles, and key accomplishments

SDE Intern

Outbox Labs

Jan 2026 - May 2026 (4 months)

Integrated email account connections across 5+ platforms using third-party APIs, Redis, and BullMQ, supporting 50k+ Google and Microsoft accounts while improving performance and reliability. Revamped the ColdMail Reseller (CMR) platform by updating legacy mailbox operations, rewriting cron jobs, and migrating backend components for better performance and maintainability.

Redis BullMQ Performance Optimization Reliability Engineering Google and Microsoft Account Integration

Data Science Intern

Praisnet Ltd

May 2024 - Aug 2024 (3 months)

Performed EDA on the Amex credit risk dataset (45k+ records) and engineered features such as credit utilization, employment duration, and credit score to improve model performance. Built and evaluated credit default prediction models using scikit-learn and XGBoost, selecting the best model based on ROC-AUC, Precision, Recall, and F1-score.

Feature Engineering Credit Risk Modeling scikit learn XGBoost Model Evaluation ROC AUC Precision Recall F1 Score

Education

Degrees, certifications, and relevant coursework

Vellore Institute of Technology

Bachelor of Technology, Computer Science and Engineering (AI & Machine Learning)

2022 - 2026

B.Tech in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning at Vellore Institute of Technology (VIT), Chennai, from Aug 2022 to April 2026.