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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. #J-18808-Ljbffr