Demo

Senior Platform Engineer

Cordia Resources by Cherry Bekaert
Arlington, VA Full Time
POSTED ON 3/4/2025
AVAILABLE BEFORE 4/26/2025

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 Parry Labs 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.

 

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