Hammad Sajid is a software engineer specializing in turning cutting-edge LLM research into cost-effective, production-grade AI for enterprise systems. Currently at GoodCore Software, he architects agentic RAG and VLM pipelines—deploying and benchmarking models like vLLM, Ollama, Qwen and NVIDIA NIM—and designed a multi-tenant Qdrant-backed vector DB used by large clients including META and NVIDIA. He previously improved executive-search precision to over 90% through LoRA/SFT/GRPO fine-tuning and prompt engineering on both open and closed models, and co-created Pakistan’s first 1B-parameter Urdu instruct-tuned LM. A top performer in SemEval and CLEF competitions with ACL-accepted work, he combines strong academic results (BS CS, 3.87/4.0) and hands-on deployment experience to bridge research and production at scale.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, 3.87/4.0, Bachelor of Science - BS, Computer Science, 3.87/4.0 at Habib University
Contributions:1 review, 32 PRs, 408 pushes in 6 years 5 months
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Hammad Sajid - Software Engineer at GoodCore Software