About
Generative AI–focused ML Engineer with an M.Tech in AI from IISc Bangalore and 3 years of experience (2.5 at Qualcomm) optimizing on-device deep learning inference (30–50% latency reduction, <1% accuracy drop). Builds agentic LLM systems (multi-agent LangGraph workflows with MCP tools and human-in-the-loop control) and Corrective RAG pipelines (hit rate 55% → 74%). Also skilled in GraphSAGE and imbalanced classification.
Skills & Expertise (21)
Work Experience
Machine Learning Engineer
Qualcomm
Sep 2020 - Present
Drove team productivity by building TeamAssist, an on-premise LangGraph helpdesk assistant with parallel RAG, Corrective RAG (CRAG) and human-approved MCP ticketing over 300+ internal docs, serving an 18-member team from a single server with a self-hosted LLM and no external APIs, so no company data left the network. Automated regression-point detection across SNPE versions with an end-to-end pipeline, replacing manual comparison. Designed low-latency deep learning pipelines on Snapdragon using SNPE (DSP/NPU backends), profiling CPU/DSP layers to isolate compute bottlenecks and speed up deployment. Streamlined PyTorch-to-DLC graph conversion, resolving operator incompatibilities and applying post-training quantization to cut inference latency by 30–50% with a <1% accuracy drop.
Machine Learning Engineer
Centre for Artificial Intelligence & Robotics (CAIR) DRDO
Mar 2020 - Sep 2020
Developed a multimodal object detection model fusing camera and radar point clouds to improve detection accuracy in low-visibility and adverse weather conditions.
Education
M.Tech in Artificial Intelligence - Indian Institute of Science (IISc), Bangalore
2020 - 2022 · Afghanistan
B.Tech in Computer Science Engineering - Institute of Engineering & Management, Kolkata
2016 - 2020 · Afghanistan
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Skills (21)
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