d
divyeshkapadiya

Divyesh

@divyeshkapadiya

Embedded Linux Firmware and IoT Expert

Indien
Englisch, Hindi, Gujarati
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
Embedded Software Engineer at Qualcomm with 2+ years of experience in Linux kernel, WLAN driver development, and GenAI-powered engineering automation. Skilled in Embedded Linux, C/C++, system debugging, MCP servers, and AI-assisted tooling for large-scale code analysis and productivity enhancement.... Mehr lesen

Kompetenzen

d
divyeshkapadiya
Divyesh
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

Eingebettete Systeme & Internet der Dinge
I will help for mock technical interview embedded systems, linux os

Arbeitserfahrung

Qualcomm

Embedded Software Engineer

Qualcomm • Vollzeit

Mar 2025 - Present1 yr 3 mos

• Designed and implemented ML-based application traffic classification feature in WLAN to enable intelligent Quality of Service (QoS), improving real-time traffic prioritization and power efficiency. • Worked on WLAN (Wi-Fi) driver development focusing on performance optimization, stability, and low-level driver enhancements using C across embedded Linux systems. • Debugged and resolved complex kernel and driver-level issues including packet drops, DMA unmap mismatches, memory leaks, and regression failures impacting system stability. • Performed crash and performance debugging using T32, identifying root causes such as buffer overflows, synchronization issues, and packet delay scenarios leading to device instability. • Analyzed and resolved customer and validation-reported issues through deep log analysis, ensuring production-ready fixes and improved WLAN reliability. Generative AI & Automation: • Built internal automation tooling for WLAN log analysis and issue triaging, reducing debugging turnaround time from 3–4 hours to 15–20 minutes. • Developed an MCP server with code indexing and tagging support for efficient symbol/API retrieval, minimizing full-file parsing and reducing LLM inference cost. • Built tooling for large-scale codebase analysis and automated feature documentation generation including flow diagrams, sequence diagrams, DSA relationships, dependency mapping, and feature-level analysis. • Worked extensively with GenAI models including Claude, Gemini, and GPT for code analysis, design optimization, code improvement, and engineering productivity automation.