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Yash Sandansing
Mid-Level Software Engineer specializing in backend, cloud, and scalable APIs
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Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.
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Key Strengths
- Built LLM/RAG assistant grounded in textbook source material
- Implemented missing preprocessing pipeline from research paper to make VGT PDF parser work in production
- Improved parsed textbook text cleanliness/reliability (~90% cleaner) by combining visual parsing with traditional PDF text extraction and image cropping
- Refactored monolithic image processing into scalable async microservices/background workers using Celery to prevent OOM and improve throughput
- Provisioned AWS EC2 compute environment optimized for GPU/CUDA workloads with S3-backed storage
- Designed Kafka-based payment webhook ingestion with strict ordering via payment-id message keys and idempotency checks
- Implemented fault-tolerant Kafka deployment with multi-zone replication
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