Senior Systems Engineer
Specializing in Linux kernel internals, QNX Neutrino IPC/RTOS, and hypervisor scheduling for next-generation automotive platforms.
I'm a Senior Systems Engineer at Qualcomm, specialising in automotive SoC performance, Linux kernel internals, QNX Neutrino IPC/RTOS, and hypervisor scheduling.
My expertise includes configuring JTAG-level hardware counter tracing, solving queueing-model problems for scheduler contention, and automating concurrent characterisation pipelines, enabling deterministic performance in automotive domains.
I enjoy engineering profiling toolkits directly interfacing with hardware counters as well as taking on complex full-system integration challenges across CPU, GPU, DDR, and NPUs.
Building and optimising systems where hardware meets software at the edge of real-world performance.
Deep expertise in Linux kernel internals, QNX Neutrino IPC/RTOS, hypervisor scheduling (KVM/QNX Hypervisor), and SoC bring-up.
Advanced granular profiling involving perf_events, flame graphs, and extracting LLCC/DDR hardware counters.
Bringing up automotive SoC (Snapdragon SA-series platforms), DDR5/LPDDR5 controller analysis, and conducting Vmin characterization pipelines.
Developing low-level profiling toolkits in C++17 and automating complex generation pipelines via production-grade Python and Bash.
A selection of projects spanning systems automation, performance engineering, and applied ML.
Engineered a custom profiling toolkit to automate flame graph generation and interface directly with hardware counters via perf_event_open() for granular IPC latency benchmarking across QNX and Linux environments.
Automated the end-to-end LLCC partition sizing problem: profiled CPU, GPU, and Multimedia client cache working sets via hardware counter sweeps, fit marginal-gain curves per client, and solved a constrained allocation over the total LLCC budget to minimise DDR bandwidth while satisfying per-client latency SLAs.
Programmatically applied the computed SCID configuration to the target board and ran the full EUC benchmark suite, producing before/after reports on DDR bandwidth utilisation and cache hit rates across subsystems.
Chauhan, A., Singh, A. "Health Insurance Recommendation using Probabilistic Data Structures" 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1-6 DOI: 10.1109/ICCCNT56998.2023.10307603.
Data Science Facilitator, GDSC JGI: Volunteered multiple workshops on basic as well as emerging Technologies (Sep 2019 - Aug 2021).
Core Team Member, GDG Jodhpur: Volunteered in DevFest - 2019 (Aug 2018 - Aug 2020).
Technical experiments leveraging agentic AI to push the boundaries of research and visualisation.
An experimental exploration into cognitive patterns and historical systems. Visualized via a bespoke 3D/2D interface designed to reveal latent connections within high-dimensional datasets.
Launch Environment →Open to conversations about systems engineering, automotive AI, or anything interesting.
arjitc12@gmail.com