I'm an AI Engineer who builds fast, cost-efficient LLM serving systems. I take inference research — KV-cache disaggregation, FP4 quantization, and RDMA-scale compute — and turn it into measurable production wins on A800/H100 clusters. I'm an M.Eng. candidate at NWPU and the author of NVFP4-DiT (IEEE TNNLS, under review).

• 🎓 AI/ML Engineer | LLM Inference & GPU Optimization | Multimodal AI Research — 2027 New Grad, open to AI/ML, Research Engineer & AI Infrastructure roles across Mainland China & Hong Kong (MNC & global AI R&D); available Jul 2027.
• 🛠️ Building an open-source AI-infra portfolio (LLM serving, KV-cache, RDMA, FP8 quantization) to sharpen and showcase production systems engineering.
• 📄 Writing my M.Eng. thesis on multimodal deepfake detection (visual + audio + temporal inconsistencies); first author of NVFP4-DiT (IEEE TNNLS, Q1, under review).

🎓 New Graduate 2027 targeting AI Infrastructure / LLM Inference engineering roles at MNC & global AI R&D centers across Mainland China + Hong Kong.

 

flowchart LR
    BD[Bangladesh] --> CN[China: Xi'an]
    CN --> BS[NWPU: BSc in CST]
    BS --> MS[NWPU: MEng in SWE]
    MS --> AI[AI Engineer]
    MS --> RS[NVFP4-DiT Research]
    AI --> PF[10-Project Open-Source Portfolio]
    RS --> PF
    PF --> FUT[The Road Ahead]

• AI Infrastructure — KV-cache architecture, prefill/decode disaggregation, SGLang/vLLM, RDMA, A800/H100 clusters.
• Low-Precision Inference — FP8/FP4 quantization for LLMs and diffusion transformers.
• M.Eng. Software Engineering @ NWPU — LLM inference optimization & multimodal AI.

• LLM Serving at Scale — KV-cache disaggregation (PD split), prefix caching & continuous batching on SGLang/vLLM across A800/H100.
• Low-Precision Inference — FP8/FP4 quantization for LLMs and diffusion transformers; author of NVFP4-DiT (IEEE TNNLS, under review).
• Distributed GPU Systems — RDMA-based multi-node training/inference and cluster orchestration.
• GPU Kernels — CUDA / Triton / FlashAttention kernels for attention and GEMM.
• Multimodal AI — audio-visual-temporal fusion for deepfake detection and video generation.

• AI Infrastructure Engineer Intern | InfiX.ai | Shenzhen, China | Apr 2026 - Jun 2026
• Software Engineer Intern (AI Agent) | Hong Kong Amram Group | Shenzhen, China | Jun 2025 - Sep 2025
• Electrical Software Engineer Intern | Shaanxi Longong Intelligent Technology | Xi'an, China | Feb 2025 - Apr 2025

• AI Infrastructure & LLM Inference Systems (KV-cache, PD disaggregation, RDMA)
• Multimodal AI (visual + audio + temporal fusion, deepfake detection, video generation)
• Low-Precision Quantization (FP8/FP4 for diffusion transformers and LLMs)
• GPU Kernel Optimization (CUDA, Triton, FlashAttention, GEMM)

• LLM serving infrastructure and distributed systems
• Multimodal AI and computer vision research
• Open-source AI tooling and frameworks
• Always happy to connect via email or LinkedIn

A curated set of 10 production-quality, fully-tested, Dockerized AI-infra projects — each with a clear architecture, quickstart, and CI. Showcased in ai-infra-portfolio.

• NVFP4-DiT: 4-bit Audio-Guided Video Diffusion Transformers — IEEE TNNLS, under review.

“Inference is where the model meets the metal — I make that intersection fast, cheap, and observable.”