Open to opportunities

Siddharth Seth

@siddharthseth

Message

I build reliable backend and AI systems, shipping production-grade features end to end.

India

Message

What I'm looking for

I’m looking for a role where I can own backend systems and real-world workflows, build offline-first experiences, and apply LLM/ML techniques—while collaborating across teams and shipping measurable improvements.

I’m a computer science engineer who enjoys taking ownership—turning requirements into resilient software that works in the real world. As a Summer Intern at Tata Power Central Odisha Distribution Limited, I built and deployed production-grade billing systems integrating Android clients with backend APIs and offline-first synchronization, reducing manual errors by 67% and improving billing efficiency by 43%.

Currently serving as a Technical Lead for the IEEE Photonics Society, I own website design, development, and maintenance for 300+ users with zero downtime, and I lead technical planning for a 300+ participant hackathon. I also explore ML and agentic workflows—building deep learning time-series forecasting systems and multi-agent pipelines like ClinSight with document ingestion, entity extraction, and an LLM-powered WhatsApp query bot.

Experience

Work history, roles, and key accomplishments

Current

Technical Lead

Current

IEEE Photonics Society

Aug 2024 - Present (1 year 10 months)

Owned design, development, and maintenance of the society website, supporting 300+ users and multiple concurrent events with zero downtime. Led technical planning and execution of a 300+ participant hackathon, managing live systems and resolving issues in real time.

Website Development System Reliability Technical Planning Hackathon Technical Execution Cross Functional Collaboration

Summer Intern

Tata Power Central Odisha Distribution Limited

May 2025 - Jul 2025 (2 months)

Built and deployed production billing systems integrating Android clients with backend APIs and offline-first data synchronization, reducing manual errors by 67% and improving billing efficiency by 43%. Designed resilient workflows for unreliable network conditions and debugged live edge cases in field environments.

Android App Integration REST APIs Offline Synchronization Billing Systems Synchronization Debugging

Research Intern

IIT Patna

May 2024 - Jun 2024 (1 month)

Developed deep learning forecasting systems trained on multi-year time-series data across six Indian megacities, improving forecast accuracy by 20%. Built preprocessing and evaluation pipelines for LSTM, GRU, and Transformer model variants to ensure reliable training under noisy real-world data.

Time Series Models Deep Learning Transformer Models data preprocessing Model Evaluation Data Pipelines Python