Professional Overview
ML Systems & Inference Performance Engineer with close to 7 years across LLM inference optimization, distributed training, and hardware-software co-design, spanning model architecture, quantization, and multimodal and video diffusion systems on NVIDIA, Intel Gaudi, and Arc/XPU GPUs. Shipped 2–60× speedups, first-of-kind model enablements, and 20+ merged open-source PRs (SGLang, bitsandbytes, optimum-habana). AAAI’21 publication in probabilistic time-series forecasting.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
