PANKAJ RAWAT

Software Engineer

Dehradun, Uttarakhand, India2 yrs 9 mos experience

Highly Stable

Key Highlights

Expert in GPU driver architecture and virtualization.
Proven track record in performance optimization.
Strong background in system-level debugging.

Stackforce AI infers this person is a GPU Software Engineer specializing in virtualization and performance optimization in the SaaS industry.

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Skills

Core Skills

Gpu Driver ArchitectureVirtualizationPerformance Optimization

Other Skills

GPU DriversSystem DebuggingPower BIArduinoMachine LearningData StructuresNumPyPandasJupyterOperating SystemsLinuxLinux KernelGitHubObject-Oriented Programming (OOP)C++

About

I am a Software Engineer with experience in GPU driver development, virtualization technologies, and system-level debugging. Currently working at Intel Corporation, I focus on building and optimizing low-level software components that power modern computing platforms. My work primarily involves graphics driver architecture, SR-IOV virtualization, and performance optimization, where I design solutions that improve system reliability, scalability, and efficiency across multiple GPU platforms. I have experience developing validation frameworks, debugging complex system-level issues, and optimizing driver workflows to enhance performance and stability. Core Areas of Interest • GPU Driver Architecture • Virtualization (SR-IOV, Hyper-V, QEMU) • System-Level Debugging • Linux Kernel & Operating Systems • Performance Optimization Technical Skills C, C++, Python • GPU Drivers • Virtualization • System Debugging • Git • WinDbg • Hyper-V • Power BI

Experience

2 yrs 9 mos

Total Experience

2 yrs 9 mos

Average Tenure

2 yrs 9 mos

Current Experience

Intel corporation

2 roles

GPU Software Development Engineer

Aug 2023 – Present · 2 yrs 9 mos · Bengaluru, Karnataka, India · On-site

Designed and implemented a GPU save/restore flow for SR-IOV virtualization, enabling reliable VM snapshot and restoration across instances while preserving GPU state integrity and memory consistency.
Built an end-to-end SR-IOV validation framework across 5+ Intel GPU platforms, increasing regression coverage and reducing driver escapes by 37%.
Optimized GPU timestamp retrieval by implementing a CPU-based extrapolation technique, reducing read latency by approximately 1.6 µs and improving logging accuracy through per-frame recalibration.
Developed interactive Power BI dashboards to monitor driver KPIs against competitive benchmarks, identifying performance bottlenecks and improving overall driver performance by 13%.

GPU DriversVirtualizationSystem DebuggingPerformance OptimizationPower BIGPU Driver Architecture

GPU SDE Intern

Jun 2022 – May 2023 · 11 mos · Bengaluru, Karnataka, India · On-site

Developed an automated validation framework using Arduino to simulate discrete GPU surprise-removal scenarios, eliminating 100% manual validation effort.
Improved the validation framework by refactoring the codebase, removing deep call stacks, and optimizing log-driven validation workflows, reducing build time by 13%.
Worked with GPU driver architecture and virtualization workflows, performing system-level debugging across integrated and discrete GPU platforms.

ArduinoGPU DriversSystem DebuggingGPU Driver Architecture