LightSolver develops quantum-inspired, laser-based supercomputers – available on-premises or over the cloud – to deliver groundbreaking performance and energy efficiency, tackling the world’s toughest computational challenges in defense, aviation, finance, logistics, and manufacturing.

Role Overview

Join LightSolver’s core system engineering team and help shape the software foundation that powers our photonic-based compute platform. You’ll work across the Linux stack — from kernel tuning to display system integration — ensuring seamless operation across hardware, cloud, and local environments. While the focus is on Linux, you’ll occasionally support Windows-based components as needed. This role bridges system-level software with cutting-edge infrastructure, offering hands-on impact in a fast-moving R&D setting. The position is hybrid, with one remote workday per week.

Responsibilities

• Integrate and optimize Linux systems with third-party drivers and hardware interfaces (e.g., cameras, PCIe, HDMI) for reliable, high-performance operation.
• Tune Linux kernel and I/O configurations to support low-latency, high-throughput compute workloads.
• Configure and maintain Linux display stacks and graphical environments (e.g., X11, Wayland, GNOME) as needed for system-level integration.
• Interface with cloud-native components (AWS, microservices) and support hybrid deployment models.
• Leverage GPU resources (e.g., CUDA) for compute and system-side acceleration tasks.
• Develop Python tooling and scripts to support diagnostics, automation, and system orchestration.
• Contribute to platform bring-up and stability across evolving software and hardware environments.

Qualifications

• B.Sc. in Computer Science, Electrical Engineering, or a related field.
• 3+ years of experience in Linux systems, embedded software, or related low-level engineering domains.
• Proficiency in C/C++.
• Strong understanding of Linux internals, including kernel behavior, boot processes, and I/O.
• Experience integrating third-party hardware drivers into production Linux environments.
• Familiarity with display protocols and desktop environments (e.g., X11, Wayland, GNOME, XFCE).
• Proficiency in Python for scripting and automation.
• Exposure to GPU programming or CUDA-based acceleration.
• Advantage: Experience with AWS or microservice-based architectures.
• Advantage: Familiarity with C# and the .NET ecosystem.
• Advantage: Familiarity with Windows systems and environments.