Summary
Rahul Dogra is a Senior Data Scientist with five years of hands-on experience building and operationalizing AI and ML systems across finance, enterprise, and product domains. He has delivered high-impact solutions—price optimization and demand forecasting with LSTM, high-throughput document ingestion and extraction pipelines, and real-time pose-estimation products—often integrating LLMs and GenAI into microservices on AWS. Pragmatic about production constraints, he combines GPU-optimized model training (PyTorch/CUDA) with robust DevOps—Docker, Jenkins, CI/CD, Lambda and Nginx—to shrink inference time and accelerate deployments. His work on selective OCR, embedding caching, chunk-level deduplication and cascaded extraction demonstrates a focus on cost-efficient, scalable pipelines rather than just model accuracy. Based in Gurugram, he pairs deep debugging instincts for complex deep learning failures with a strong toolkit spanning text/image processing, vector DBs and transformers. Notably, he has repeatedly translated research ideas into production features that boosted throughput and cut costs while maintaining high accuracy.
5 years of coding experience
6 years of employment as a software developer
Post Graduation Diploma in Banking Operations Banking, Post Graduation Diploma in Banking Operations Banking at NIIT Pune
BCA Computer Science, BCA Computer Science at University of Lucknow
English, Hindi