We’re looking for an experienced GPGPU Engineer to lead the development of a cloud-based, ARM and x86-compatible virtual environment. This role will focus on configuring, optimizing, and managing an emulated infrastructure to support hardware, enabling seamless development and testing in a fully virtualized environment.

 

Duties and Responsibilities

• Lead the configuration, optimization, and management of ARM-based cloud instances (e.g., AWS Graviton) to support emulation for both ARM and x86/GPU platforms.
• Develop multi-architecture, cross-compiled containers, utilizing Docker Buildx and GCC toolchains, to support GPGPU emulation and facilitate scalability.
• Collaborate closely with software and hardware teams to ensure all drivers, applications, and dependencies are optimized for a hybrid ARM/x86 emulated environment.
• Establish and manage container orchestration (e.g., K3s, Kubernetes) for OCI-compliant containers, focusing on efficient GPU access and seamless cross-platform compatibility.
• Provide guidance on ARM and x86 cross-compilation practices, ensuring performance, security, and scalability across the virtualized development lifecycle.
• Work with network engineers to integrate SDWAN within the emulation environment, meeting high-bandwidth, low-latency requirements.
• Enhance security and compliance by hardening cross-architecture container environments, specifically around GPU access and data handling.
• Other duties as assigned.

 

Required Qualifications

• 5+ years of experience with ARM architecture, multi-architecture containerization, and cross-compilation.
• Strong expertise with AWS services, particularly those supporting ARM and GPU (e.g., AWS Graviton, G4DN, bare metal instances).
• Proficiency with cross-compilation toolchains (GCC, LLVM) and in building OCI-compliant multi-architecture containers.
• Experience with NVIDIA GPU drivers, CUDA libraries, and managing GPU access in containerized setups.
• Skilled in K3s, Kubernetes, or similar container orchestration solutions.
• Familiarity with SDWAN configurations and best practices for hybrid cloud networks.
• Advanced understanding of Linux-based systems, including low-level hardware interactions and device drivers.

 

Preferred Qualifications

• Hands-on experience with ARM-based hardware emulation tools like QEMU.
• Background in high-performance computing (HPC) and managing GPU-accelerated workloads.
• Knowledge of security best practices in virtualized and containerized environments.
• Previous experience with multi-cloud or hybrid cloud deployments.