Kashiful Haque is a Machine Learning Engineer with 8 years of software experience and 4 years focused on production ML systems, currently building agent tooling and execution-layer infrastructure at Wand AI. He has hands-on expertise tuning and deploying large models (e.g., Mistral-7B via QLoRA), optimizing high-throughput inference with vLLM, and engineering scalable RAG and LLM→SQL agent pipelines that prioritize latency and robustness. Past roles include architecting low-latency streaming and hybrid semantic search systems at American Express and migrating monoliths to microservices during internships, demonstrating fluency across system design, infra, and model engineering. He combines pragmatic engineering—helm/Jenkins/OpenShift deployments, dynamic batching, quantized kernels—with careful evaluation pipelines and test harnesses to make ML outputs auditable and reliable. Based in Bengaluru and trained at IIT Madras in Data Science, he enjoys turning numerical code into systems that make machines decidedly smarter.
Contributions:110 commits, 62 PRs, 98 pushes in 2 years
apivue-jsweather-appjavascriptvue
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Kashiful Haque - Machine Learning Engineer at Wand AI